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Let's go. Datafam this is the
main keynote stage three in
main keynote stage three in
Thompson. Seeing is just the
Thompson. Seeing is just the
beginning because what you see
beginning because what you see
shapes what you believe. And
shapes what you believe. And
what you believe. Well, that
what you believe. Well, that
shapes what you do. 25 years
shapes what you do. 25 years
ago, tableau began with a
ago, tableau began with a
simple idea. If people could
simple idea. If people could
truly see their data, they
truly see their data, they
could understand it. And that
could understand it. And that
changed everything. Now, the
changed everything. Now, the
real story was never the
real story was never the
dashboards. It was the people
dashboards. It was the people
behind them. You, the datafam,
behind them. You, the datafam,
the ones who asked better
the ones who asked better
questions, who challenged
questions, who challenged
assumptions, who didn't settle
assumptions, who didn't settle
for good enough. You made data
for good enough. You made data
something people could trust.
something people could trust.
And because of that, entire
And because of that, entire
organizations changed, systems
organizations changed, systems
evolved outcomes got better,
evolved outcomes got better,
and the world moved forward.
and the world moved forward.
Because you did look at where
Because you did look at where
we are now. The distance
we are now. The distance
between knowing and doing it
between knowing and doing it
matters more than ever. We've
matters more than ever. We've
entered a new era. A world
entered a new era. A world
where data does not wait, where
where data does not wait, where
intelligence does not sit in a
intelligence does not sit in a
dashboard. It moves with you,
dashboard. It moves with you,
for you, for the systems you
for you, for the systems you
trust. Don't just explain
trust. Don't just explain
what's happening. They help you
what's happening. They help you
shape what happens next. This
shape what happens next. This
is what it means to be a
is what it means to be a
genetic. Just see, it's not
genetic. Just see, it's not
just understanding, but acting
just understanding, but acting
in the moments that matter. The
in the moments that matter. The
gap between question and action
gap between question and action
gone. Because the future is not
gone. Because the future is not
something you wait for. It's
something you wait for. It's
something you create. Now look,
something you create. Now look,
you've done it before and
you've done it before and
you're about to do it again. So
you're about to do it again. So
what happens next? That's up to
what happens next? That's up to
you. Please welcome Executive
you. Please welcome Executive
Vice President and Chief
Vice President and Chief
Product Officer Tableau
Product Officer Tableau
Southard Jones DC. Hello, TC.
Southard Jones DC. Hello, TC.
Woo! Welcome. Welcome to the
Woo! Welcome. Welcome to the
beautiful sunny city of San
beautiful sunny city of San
Diego. And welcome to the
Diego. And welcome to the
world's largest and greatest
world's largest and greatest
data and analytics event. And
data and analytics event. And
what makes it the greatest, all
what makes it the greatest, all
of you, this community, the
of you, this community, the
Datafam who. I want to start by
Datafam who. I want to start by
thanking you, thanking everyone
thanking you, thanking everyone
here in person for taking time
here in person for taking time
out of your busy schedule,
out of your busy schedule,
traveling long distances. We've
traveling long distances. We've
had people from Australia,
had people from Australia,
Japan, Europe, Africa, South
Japan, Europe, Africa, South
America, everybody has come
America, everybody has come
here for this community and
here for this community and
thank you for those online. I
thank you for those online. I
think we have like 20,000
think we have like 20,000
people on Salesforce+. Thank
people on Salesforce+. Thank
you for joining us virtually,
you for joining us virtually,
and I want to take a moment to
and I want to take a moment to
thank a few special groups, a
thank a few special groups, a
few groups that make this
few groups that make this
community really what it is. So
community really what it is. So
when I call out your name,
when I call out your name,
please stand. I want to thank
please stand. I want to thank
our visionaries first. If
our visionaries first. If
you're a visionary, please
you're a visionary, please
stand up, be recognized. Who?
stand up, be recognized. Who?
Thank you for leading us
Thank you for leading us
forward with your innovative
forward with your innovative
thoughts and driving our
thoughts and driving our
product forward and driving
product forward and driving
this community forward. There's
this community forward. There's
a couple of you I want to
a couple of you I want to
recognize specifically because
recognize specifically because
you've been a visionary for
you've been a visionary for
five years and you've done some
five years and you've done some
other amazing things for us,
other amazing things for us,
and that makes you a Hall of
and that makes you a Hall of
Famer. So. Tristan Galvan yes,
Famer. So. Tristan Galvan yes,
Tristan. Thank you. Zach Bowers.
Tristan. Thank you. Zach Bowers.
Zach thank you. Engine. Thank
Zach thank you. Engine. Thank
you. Next, if you're an
you. Next, if you're an
ambassador I'd like you to
ambassador I'd like you to
stand. Please stand up
stand. Please stand up
ambassador visionary stay
ambassador visionary stay
standing. Ambassador who? This
standing. Ambassador who? This
is so cool to see. Your
is so cool to see. Your
evangelism, your ability to
evangelism, your ability to
bring people together and share
bring people together and share
your passion has made this
your passion has made this
event what it is. Many people
event what it is. Many people
are in this room because of you.
are in this room because of you.
So thank you. Thank you. Great
So thank you. Thank you. Great
appreciation and gratitude.
appreciation and gratitude.
Stay standing. Next, we want to
Stay standing. Next, we want to
thank Tableau user Group
thank Tableau user Group
leaders. If you have organized
leaders. If you have organized
your user group, if you
your user group, if you
presented at a user group, or
presented at a user group, or
if you've just been somebody
if you've just been somebody
who's taught others, please
who's taught others, please
stand and be recognized.
stand and be recognized.
Question. Thank you. Thank you.
Question. Thank you. Thank you.
It's a passion for sharing and
It's a passion for sharing and
teaching that makes this
teaching that makes this
community what it is. Without
community what it is. Without
you, people wouldn't be
you, people wouldn't be
building data skills, which are
building data skills, which are
some of our greatest life
some of our greatest life
skills. So a huge thank you as
skills. So a huge thank you as
well. You've all taken us on
well. You've all taken us on
this amazing journey. You can
this amazing journey. You can
stay seated now, but thank you.
stay seated now, but thank you.
You're all brought us to this
You're all brought us to this
great journey. We've been on
great journey. We've been on
this journey for quite some
this journey for quite some
time, and the journey started
time, and the journey started
for many of us as a first timer
for many of us as a first timer
at an event. So if you're a
at an event. So if you're a
first timer, I'd like you to
first timer, I'd like you to
stand up. Now, who here is the
stand up. Now, who here is the
Tableau conference? First time
Tableau conference? First time
event, first time stand up. Wow,
event, first time stand up. Wow,
really? This is awesome. Look
really? This is awesome. Look
at this. Look at that. Wow.
at this. Look at that. Wow.
Wait, wait. Stay standing. Turn
Wait, wait. Stay standing. Turn
to your right or turn to your
to your right or turn to your
left. Give a fist pump or shake
left. Give a fist pump or shake
your hands. Right here. This
your hands. Right here. This
moment is what this event is
moment is what this event is
about. It's about sharing your
about. It's about sharing your
passion. It's about meeting new
passion. It's about meeting new
people. It's about making
people. It's about making
acquaintances, making friends.
acquaintances, making friends.
Some of you might even meet
Some of you might even meet
your future spouse. That's
your future spouse. That's
happened. It has happened. So
happened. It has happened. So
thank you for coming out and
thank you for coming out and
stepping outside, outside your
stepping outside, outside your
comfort zone and making
comfort zone and making
yourself available to meet new
yourself available to meet new
people. That's what this event
people. That's what this event
is all about. That's what this
is all about. That's what this
community is all about. This.
community is all about. This.
You can take a seat. Thank you.
You can take a seat. Thank you.
So this journey started in
So this journey started in
Seattle. It started with 187
Seattle. It started with 187
people at our first event.
people at our first event.
Imagine 187. There's like 6000
Imagine 187. There's like 6000
people here. There's 20,000
people here. There's 20,000
online, 187 people to where we
online, 187 people to where we
are now. And that is that
are now. And that is that
journey went across the globe.
journey went across the globe.
And because of you, we've
And because of you, we've
reached so many different
reached so many different
people. Because of you, we've
people. Because of you, we've
been able to reach
been able to reach
underdeveloped countries. We've
underdeveloped countries. We've
been able to reach new and
been able to reach new and
unknown places that had never
unknown places that had never
even worked with data before.
even worked with data before.
Because of you, we are in 48
Because of you, we are in 48
countries today over millions
countries today over millions
of people, 210 user groups,
of people, 210 user groups,
57,000 user group members,
57,000 user group members,
70,000 events on a monthly
70,000 events on a monthly
basis, and almost every single
basis, and almost every single
one of them, because somebody
one of them, because somebody
here online is organizing it
here online is organizing it
and setting up and sharing
and setting up and sharing
their passion for what we all
their passion for what we all
want to do is help people see,
want to do is help people see,
understand and act on data.
understand and act on data.
Such a massive thank you. And
Such a massive thank you. And
that's the power of this
that's the power of this
community. That's what this
community. That's what this
event is about. And that's what
event is about. And that's what
we're here to talk about over
we're here to talk about over
the last couple of days. Now,
the last couple of days. Now,
it's not just about the
it's not just about the
community. It is a little bit
community. It is a little bit
about this product called
about this product called
Tableau. And you guys have made
Tableau. And you guys have made
that Tableau product great. You
that Tableau product great. You
started by asking for Tableau
started by asking for Tableau
Public. So we made Tableau
Public. So we made Tableau
Public. Thank you for all those
Public. Thank you for all those
who pushed for it. And thank
who pushed for it. And thank
you, Jack McKinley for this.
you, Jack McKinley for this.
Really cool videos on Tableau
Really cool videos on Tableau
Public. It shows all the
Public. It shows all the
features we've been releasing
features we've been releasing
over time. And it's beautiful.
over time. And it's beautiful.
Viz. That's just an example of
Viz. That's just an example of
what Tableau Public is. It is
what Tableau Public is. It is
often the place where all of us
often the place where all of us
have brought light to the
have brought light to the
causes that we have passion in
causes that we have passion in
our hearts about. I still think
our hearts about. I still think
it's one of the best properties
it's one of the best properties
on the online there is today
on the online there is today
wasn't just public. You asked
wasn't just public. You asked
for something else. You said,
for something else. You said,
hey, can you make visual
hey, can you make visual
analytics better? Can you bring
analytics better? Can you bring
us Tableau free desktop? Yes,
us Tableau free desktop? Yes,
that's what we did. That's what
that's what we did. That's what
we did. And get this, a hundred
we did. And get this, a hundred
thousand people have downloaded
thousand people have downloaded
Tableau Free Desktop since
Tableau Free Desktop since
March 1st hundred 000 people
March 1st hundred 000 people
who previously had not been
who previously had not been
exposed to tableau and now are
exposed to tableau and now are
being exposed to tableau. And
being exposed to tableau. And
that's because of us listening
that's because of us listening
to you and together leading
to you and together leading
Forward this evolution. It
Forward this evolution. It
wasn't just that you asked her
wasn't just that you asked her
a bunch of features in our
a bunch of features in our
product. You asked for rounded
product. You asked for rounded
corners, custom color palettes.
corners, custom color palettes.
Yes. Rounded corners, road TIME
Yes. Rounded corners, road TIME
areas in tableau maps. My new
areas in tableau maps. My new
favorite feature. All of them
favorite feature. All of them
because of you and us together
because of you and us together
leading that charge. But today.
leading that charge. But today.
Today, you can't go anywhere
Today, you can't go anywhere
without someone talking about
without someone talking about
AI. And you know what? You know
AI. And you know what? You know
who's leading that. We are, you
who's leading that. We are, you
are. I see you out there. I see
are. I see you out there. I see
you on LinkedIn. VP coding.
you on LinkedIn. VP coding.
Connecting to Tableau MCP.
Connecting to Tableau MCP.
Building custom apps,
Building custom apps,
leveraging Tableau AI. I see
leveraging Tableau AI. I see
you leading the future. And yes,
you leading the future. And yes,
there's a lot of uncertainty
there's a lot of uncertainty
because there's so much hype,
because there's so much hype,
but that's something I want
but that's something I want
everyone here to take away.
everyone here to take away.
Next three days, you're going
Next three days, you're going
to learn a lot about how AI can
to learn a lot about how AI can
accelerate our mission to help
accelerate our mission to help
people see and understand data.
people see and understand data.
But there's one thing AI cannot
But there's one thing AI cannot
do that all of you have already
do that all of you have already
done. Anytime someone logs into
done. Anytime someone logs into
tableau and looks at a vase or
tableau and looks at a vase or
a dashboard or a metric, do you
a dashboard or a metric, do you
know why they trust it? Do you
know why they trust it? Do you
know why? Because someone here
know why? Because someone here
has gone to great lengths to
has gone to great lengths to
make sure it's correct. Someone
make sure it's correct. Someone
here has said, I'm going to
here has said, I'm going to
make sure the join is correct.
make sure the join is correct.
I'm going to make sure the
I'm going to make sure the
level of detail calculation is
level of detail calculation is
accurate. I'm going to make
accurate. I'm going to make
sure the visual representation
sure the visual representation
is right. I am personally going
is right. I am personally going
to make sure that someone can
to make sure that someone can
trust this because they make
trust this because they make
key decisions on that. AI can't
key decisions on that. AI can't
do that. Only you can. So for
do that. Only you can. So for
the next couple of days, you're
the next couple of days, you're
going to learn a lot about AI.
going to learn a lot about AI.
You'll learn about tableau
You'll learn about tableau
features. You're going to learn
features. You're going to learn
about how together we're going
about how together we're going
to accelerate our mission with
to accelerate our mission with
AI. Now, right now I need
AI. Now, right now I need
somebody who's going to help
somebody who's going to help
you, take you on that, on that
you, take you on that, on that
journey. But first, he's
journey. But first, he's
somebody who has spent his life
somebody who has spent his life
in tableau making key business
in tableau making key business
decisions based on information
decisions based on information
and knowledge that came from
and knowledge that came from
tableau. So that I want to
tableau. So that I want to
welcome our new GM for tableau,
welcome our new GM for tableau,
Mark Recker. Thank you. Thank
Mark Recker. Thank you. Thank
you, southern. Wow. I am
you, southern. Wow. I am
thrilled to be here at TC. This
thrilled to be here at TC. This
is my 55th day in this GM
is my 55th day in this GM
position, and I want to start
position, and I want to start
with a thank you, a thank you
with a thank you, a thank you
to our customers, and thank you
to our customers, and thank you
to our partners. I thank you to
to our partners. I thank you to
the incredible tableau team.
the incredible tableau team.
But most importantly, if you're
But most importantly, if you're
part of the Datafam, can you
part of the Datafam, can you
stand up? Can we give them a
stand up? Can we give them a
really, really loud. Thank you.
really, really loud. Thank you.
TC is about you. It's about the
TC is about you. It's about the
Datafam. And listen, I've been
Datafam. And listen, I've been
looking forward to this day for
looking forward to this day for
a very long time. It's actually
a very long time. It's actually
the first thing I told my team.
the first thing I told my team.
I said, we have 55 days until
I said, we have 55 days until
TC. You can ask them. They're
TC. You can ask them. They're
right over there. But I wanted
right over there. But I wanted
to be here in San Diego. As we
to be here in San Diego. As we
shape the future of Tableau
shape the future of Tableau
together now, I've had the
together now, I've had the
opportunity to meet many of you
opportunity to meet many of you
in the last 55 days, but not
in the last 55 days, but not
all of you, because we know
all of you, because we know
data. There's thousands of
data. There's thousands of
people here that would be
people here that would be
statistically improbable. Just
statistically improbable. Just
yesterday, I had coffee with
yesterday, I had coffee with
some folks. I ran into folks
some folks. I ran into folks
and saw the power of this
and saw the power of this
community and this conference.
community and this conference.
But you all don't know me yet.
But you all don't know me yet.
So what's the first thing you
So what's the first thing you
should know about me? Well, I
should know about me? Well, I
have been data obsessed since
have been data obsessed since
before I can remember. I was
before I can remember. I was
the kid scouring through box
the kid scouring through box
scores, trying to understand
scores, trying to understand
patterns in signals to
patterns in signals to
understand why my Minnesota
understand why my Minnesota
Twins were always losing, which
Twins were always losing, which
was most bad pitching and bad
was most bad pitching and bad
hitting. It's a bad combination,
hitting. It's a bad combination,
but I love data, I love it, I
but I love data, I love it, I
love the visuals, the stories
love the visuals, the stories
it tells, how it sparks
it tells, how it sparks
curiosity and the the core
curiosity and the the core
belief that I have that has
belief that I have that has
shaped my career is that when
shaped my career is that when
you can see and understand data,
you can see and understand data,
you make better decisions. And
you make better decisions. And
so for the better part of the
so for the better part of the
past decade, my day has started
past decade, my day has started
in the same place. Do you want
in the same place. Do you want
to guess Tableau a cup of philz
to guess Tableau a cup of philz
coffee and my Tableau Command
coffee and my Tableau Command
Center. Now the Phil's part is
Center. Now the Phil's part is
an unhealthy and expensive
an unhealthy and expensive
habit, so I don't recommend it.
habit, so I don't recommend it.
But Tableau Tableau would tell
But Tableau Tableau would tell
me what changed, what needed
me what changed, what needed
actions, what decisions were
actions, what decisions were
ahead in my day. So I ran my
ahead in my day. So I ran my
business on Tableau. I grew my
business on Tableau. I grew my
career on Tableau. So I think I
career on Tableau. So I think I
can safely say that I have been
can safely say that I have been
the datafam number one data fan.
the datafam number one data fan.
Now today we have more
Now today we have more
opportunity with data and
opportunity with data and
analytics than we have ever had
analytics than we have ever had
before, and that is an
before, and that is an
incredible, incredible
incredible, incredible
opportunity that we get to
opportunity that we get to
channel for the next three days
channel for the next three days
here. And that's why we come
here. And that's why we come
here to San Diego every single
here to San Diego every single
year to innovate, to be curious,
year to innovate, to be curious,
to push the boundaries of what
to push the boundaries of what
we can do together. Now, last
we can do together. Now, last
year, we showed you this slide.
year, we showed you this slide.
We introduced a gigantic
We introduced a gigantic
analytics building on the 20
analytics building on the 20
year journey of the Datafam and
year journey of the Datafam and
Tableau. Look at the eras that
Tableau. Look at the eras that
we've conquered before
we've conquered before
self-service analytics, visual
self-service analytics, visual
augmented, and in each of those
augmented, and in each of those
eras, it was you, the Datafam,
eras, it was you, the Datafam,
that took data and turned it
that took data and turned it
into insights in the form of
into insights in the form of
visits, dashboards, alerts,
visits, dashboards, alerts,
notifications, triggers so that
notifications, triggers so that
a human could take them and
a human could take them and
make decisions and take actions.
make decisions and take actions.
But guess what? The audience
But guess what? The audience
for our work is expanding in
for our work is expanding in
the future. It's not just going
the future. It's not just going
to be humans. It will, but it's
to be humans. It will, but it's
going to be humans and Agents
going to be humans and Agents
Agents you create Tableau agent,
Agents you create Tableau agent,
third party agents, and that
third party agents, and that
requires more from us because
requires more from us because
we know this data alone is not
we know this data alone is not
enough for an agent. In every
enough for an agent. In every
era of analytics, there has
era of analytics, there has
been a human on the other side
been a human on the other side
of those insights who had the
of those insights who had the
intuition to look and say,
intuition to look and say,
that's not accurate because
that's not accurate because
they have context. Raise your
they have context. Raise your
hand. I would expect every hand
hand. I would expect every hand
to go up. If you've ever looked
to go up. If you've ever looked
at a data set or dashboard and
at a data set or dashboard and
said, God, that is not accurate.
said, God, that is not accurate.
I'm going to have to spend more
I'm going to have to spend more
time on that. Yeah, we've all
time on that. Yeah, we've all
felt it. Guess what? An agent
felt it. Guess what? An agent
doesn't know that because they
doesn't know that because they
don't have context. And that is
don't have context. And that is
exactly why 89% of leaders say
exactly why 89% of leaders say
they've experienced inaccurate
they've experienced inaccurate
or misleading AI outputs. Show
or misleading AI outputs. Show
me the other 11%. So what does
me the other 11%. So what does
that mean? What does what do
that mean? What does what do
agents actually need? They need
agents actually need? They need
more. They need knowledge. They
more. They need knowledge. They
need metrics. They need
need metrics. They need
definitions. They need
definitions. They need
semantics. They need published
semantics. They need published
data sources. Is this sounding
data sources. Is this sounding
familiar? It should, because
familiar? It should, because
for the last 20 years, it has
for the last 20 years, it has
been the datafam that has been
been the datafam that has been
architecting knowledge inside
architecting knowledge inside
of Tableau in the form of in.
of Tableau in the form of in.
This statistic shocks me every
This statistic shocks me every
time. 33 million semantic data
time. 33 million semantic data
models that you built in
models that you built in
tableau. So all this era
tableau. So all this era
requires and inspires new ways
requires and inspires new ways
of thinking, new ways we can
of thinking, new ways we can
orchestrate data in analytics.
orchestrate data in analytics.
It requires one thing above
It requires one thing above
everything else, and that's
everything else, and that's
knowledge. The very knowledge
knowledge. The very knowledge
you've built in tableau. And so
you've built in tableau. And so
that's why I'm excited to
that's why I'm excited to
unveil to you where we're
unveil to you where we're
headed with tableau. Based on
headed with tableau. Based on
what you've already built
what you've already built
inside of it. So today, tableau
inside of it. So today, tableau
is your agentic analytics
is your agentic analytics
platform. Now, every layer of
platform. Now, every layer of
this platform is powered by AI,
this platform is powered by AI,
and show is way better than
and show is way better than
tell. So we're going to show
tell. So we're going to show
you for about 40 minutes. We
you for about 40 minutes. We
have some fantastic demos and
have some fantastic demos and
we're going to show you that
we're going to show you that
it's in every product
it's in every product
experience, not just tableau.
experience, not just tableau.
Next, I will repeat that, not
Next, I will repeat that, not
just tableau next. I figured
just tableau next. I figured
that would be popular. It will
that would be popular. It will
be in cloud, in server, in
be in cloud, in server, in
desktop. But before we show you,
desktop. But before we show you,
yeah, you can, you can do
yeah, you can, you can do
applause. All right. Before we
applause. All right. Before we
show you, you have to listen to
show you, you have to listen to
me because there's four things
me because there's four things
I want to highlight that you're
I want to highlight that you're
going to see. The first is our
going to see. The first is our
knowledge engine, the ability
knowledge engine, the ability
for you to take structured and
for you to take structured and
now unstructured data and in
now unstructured data and in
natural language, turn that
natural language, turn that
into knowledge and semantic
into knowledge and semantic
data models. Number two is the
data models. Number two is the
knowledge graph. So you can
knowledge graph. So you can
take in understand your entire
take in understand your entire
enterprise's knowledge base
enterprise's knowledge base
because we know there are not
because we know there are not
insights or actions without
insights or actions without
knowledge. And this is point
knowledge. And this is point
number two. Our decisions
number two. Our decisions
engine. This era is no longer
engine. This era is no longer
about insights decoupled from
about insights decoupled from
actions. It's about insights
actions. It's about insights
and actions in real time by
and actions in real time by
humans and agents alike. And
humans and agents alike. And
you will see that you will see
you will see that you will see
conversational agentic
conversational agentic
analytics in cloud, in server
analytics in cloud, in server
in. Next you will see Tableau
in. Next you will see Tableau
Pulse. You will see third party
Pulse. You will see third party
agents driving decisions
agents driving decisions
because that's what we do with
because that's what we do with
knowledge. And the third point,
knowledge. And the third point,
and this is very, very exciting.
and this is very, very exciting.
And I think it's aligned to
And I think it's aligned to
Tableau's founding principles
Tableau's founding principles
of democratizing data and trust,
of democratizing data and trust,
which is you can take your
which is you can take your
trusted knowledge anywhere,
trusted knowledge anywhere,
wherever your organization is
wherever your organization is
working through headless
working through headless
analytics and MCP. Will Sutton
analytics and MCP. Will Sutton
is going to show you, you can
is going to show you, you can
take it to Claude, you can take
take it to Claude, you can take
it to ChatGPT, to Slack. You
it to ChatGPT, to Slack. You
can even take it to Microsoft
can even take it to Microsoft
Teams. Salesforce and Tableau.
Teams. Salesforce and Tableau.
So that gives you the power as
So that gives you the power as
a datafam to tell your
a datafam to tell your
organization what they need to
organization what they need to
know before they even
know before they even
understand. They need to know
understand. They need to know
it. And this fourth point,
it. And this fourth point,
which I think in the AI era is
which I think in the AI era is
more important than ever, is
more important than ever, is
our platform is secure
our platform is secure
governance, composable, and
governance, composable, and
extensible. So you can safely
extensible. So you can safely
take your trusted knowledge
take your trusted knowledge
wherever your organization is
wherever your organization is
working. And guess what? Any
working. And guess what? Any
assets or knowledge you're
assets or knowledge you're
building elsewhere, you can
building elsewhere, you can
bring that back in to your
bring that back in to your
trusted agentic analytics and
trusted agentic analytics and
knowledge platform. Okay, so
knowledge platform. Okay, so
what does this mean for us? I
what does this mean for us? I
had a favorite line in the
had a favorite line in the
video. It was never about the
video. It was never about the
data or the dashboards. It was
data or the dashboards. It was
about you, the datafam. And in
about you, the datafam. And in
this era of AI, with all of
this era of AI, with all of
this noise, that rings truer to
this noise, that rings truer to
me than ever before. Now, we
me than ever before. Now, we
showed you this slide last year,
showed you this slide last year,
but frankly, we were a bit
but frankly, we were a bit
nebulous about it. And that's
nebulous about it. And that's
okay, because a year later,
okay, because a year later,
it's getting clearer and
it's getting clearer and
clearer. We have many fantastic
clearer. We have many fantastic
roles inside of the Datafam,
roles inside of the Datafam,
and in the future, they're
and in the future, they're
likely going to converge a
likely going to converge a
little bit in an empowering way,
little bit in an empowering way,
turning you into a more
turning you into a more
technology forward function.
technology forward function.
Now, you have always been a
Now, you have always been a
trusted enabler in Outcome
trusted enabler in Outcome
Whisperer, a decisions
Whisperer, a decisions
orchestrator, but in the future,
orchestrator, but in the future,
you're an architect, your
you're an architect, your
decisions architect, you're a
decisions architect, you're a
knowledge architect, and that
knowledge architect, and that
is empowering you to drive more
is empowering you to drive more
impact than you ever have
impact than you ever have
before. You are the composer
before. You are the composer
driving your company's entire
driving your company's entire
analytics and data strategy,
analytics and data strategy,
and that is a multiplier to the
and that is a multiplier to the
massive impact you already
massive impact you already
provide to your organizations.
provide to your organizations.
So what does all of this mean
So what does all of this mean
for us, for tableau and for the
for us, for tableau and for the
Datafam? It means the same
Datafam? It means the same
thing it did 20 years ago. It
thing it did 20 years ago. It
means opportunity. And so for
means opportunity. And so for
the next three days, we'll
the next three days, we'll
start building that future
start building that future
together, as we always have
together, as we always have
through every era of analytics.
through every era of analytics.
So guess what? The tale part is
So guess what? The tale part is
over. We're going to show you
over. We're going to show you
across every product experience,
across every product experience,
how we architect knowledge, how
how we architect knowledge, how
we power decisions, and how we
we power decisions, and how we
identify actions. But before we
identify actions. But before we
do, I would like to end the
do, I would like to end the
same way I started. The last 55
same way I started. The last 55
days have been incredibly
days have been incredibly
inspiring to me. I'm wildly
inspiring to me. I'm wildly
excited about our future, but
excited about our future, but
I'm most excited to build it
I'm most excited to build it
with you. So thank you to the
with you. So thank you to the
Datafam. Thank you to our
Datafam. Thank you to our
customers. Thank you to our
customers. Thank you to our
partners. Thank you to the
partners. Thank you to the
incredible tableau Team. And
incredible tableau Team. And
with that, Southard Jones. All
with that, Southard Jones. All
right. Thank you, Mark. And
right. Thank you, Mark. And
just as Mark said, we are going
just as Mark said, we are going
to show you product. Now that's
to show you product. Now that's
the fun part. But we're just a
the fun part. But we're just a
little bit different this year.
little bit different this year.
Instead of a tableau product or
Instead of a tableau product or
engineering people showing you
engineering people showing you
product, you get to see that
product, you get to see that
with devs on stage. Coming up
with devs on stage. Coming up
soon. Tomorrow, today. Yes, I'm
soon. Tomorrow, today. Yes, I'm
excited for that too. Today
excited for that too. Today
we're actually gonna have
we're actually gonna have
people from this audience,
people from this audience,
customers of Tableau and
customers of Tableau and
community members of Q show the
community members of Q show the
product. So I'm going to start
product. So I'm going to start
by bringing on stage someone
by bringing on stage someone
who's been with tableau for
who's been with tableau for
quite some time. Please join me
quite some time. Please join me
in welcoming the VP of Global
in welcoming the VP of Global
Retail Analytics, Chad Stroup.
Retail Analytics, Chad Stroup.
Chad, come on up. Chad, good to
Chad, come on up. Chad, good to
see you. Thanks so much for
see you. Thanks so much for
being here. Really appreciate
being here. Really appreciate
everything you've done.
everything you've done.
Disney's been a amazing leader
Disney's been a amazing leader
and a, you know, at the
and a, you know, at the
forefront of data analytics for
forefront of data analytics for
quite some time. So I really
quite some time. So I really
appreciate you coming here to
appreciate you coming here to
present. Yeah. Thank you, thank
present. Yeah. Thank you, thank
you. I appreciate it. If we're
you. I appreciate it. If we're
going to do this journey, we
going to do this journey, we
got to do it right. And so what
got to do it right. And so what
I brought was stitch. I heard
I brought was stitch. I heard
that might be your favorite
that might be your favorite
character. That's supposed to
character. That's supposed to
be me. That's you. Right.
be me. That's you. Right.
Chaotic, mischievous, chaotic
Chaotic, mischievous, chaotic
problem. Causer. It's in
problem. Causer. It's in
trouble. But a disruptor, right,
trouble. But a disruptor, right,
of the market. And in the end,
of the market. And in the end,
everybody loves stitch, right?
everybody loves stitch, right?
So here we go. Oh, boy. You
So here we go. Oh, boy. You
might need to do that. You can
might need to do that. You can
hold it. I'm going to be Groot.
hold it. I'm going to be Groot.
Oh, baby. Groot, deeply rooted
Oh, baby. Groot, deeply rooted
in data, but continuously
in data, but continuously
growing. We got to do it right.
growing. We got to do it right.
This is awkward. Oh, and a
This is awkward. Oh, and a
special thanks to my account
special thanks to my account
manager, Eddie here. He's the
manager, Eddie here. He's the
force. So he's got a baby Grogu.
force. So he's got a baby Grogu.
So, yes, let's do this. Thank
So, yes, let's do this. Thank
you. Now that I'm embarrassed
you. Now that I'm embarrassed
and red faced, I'm supposed to
and red faced, I'm supposed to
ask you some questions. No. In
ask you some questions. No. In
all seriousness, you know,
all seriousness, you know,
you've always pushed just in
you've always pushed just in
terms of where you want to take
terms of where you want to take
Tableau and how your users are
Tableau and how your users are
using it, maybe you can share a
using it, maybe you can share a
little bit about what we could
little bit about what we could
do better with Tableau today to
do better with Tableau today to
help your users be even more
help your users be even more
powerful. Sure. Thanks. Well,
powerful. Sure. Thanks. Well,
great Mark, for sharing the
great Mark, for sharing the
early vision here. It's exactly
early vision here. It's exactly
what we're looking for. So at
what we're looking for. So at
Disney, what we're thinking
Disney, what we're thinking
about is how do we get away
about is how do we get away
from the reporting layer to a
from the reporting layer to a
decision layer? Exactly what
decision layer? Exactly what
you kind of mentioned there. So
you kind of mentioned there. So
for us, it's really important
for us, it's really important
to be connected to the systems
to be connected to the systems
that are making the decisions,
that are making the decisions,
right? Today, there's a bit of
right? Today, there's a bit of
a gap. Our users are in the
a gap. Our users are in the
tool, they're looking at
tool, they're looking at
dashboards. Then our location
dashboards. Then our location
planners, for example, might be
planners, for example, might be
going down Main Street early in
going down Main Street early in
the morning. Walking through
the morning. Walking through
the Emporium, they saw a
the Emporium, they saw a
dashboard, said, okay, here's
dashboard, said, okay, here's
our top sellers, here's out of
our top sellers, here's out of
stock. But then they got to go
stock. But then they got to go
back to the office and then
back to the office and then
they got to make the decision.
they got to make the decision.
What do I do? How do I, you
What do I do? How do I, you
know, make that guest
know, make that guest
experience better? And so what
experience better? And so what
we're asking is how do we get
we're asking is how do we get
that closer and connected to
that closer and connected to
the systems where I'm actually
the systems where I'm actually
making change? So that's for us
making change? So that's for us
is if we can do that continuous
is if we can do that continuous
loop, bring us closer to that
loop, bring us closer to that
real time, that would make a
real time, that would make a
big difference for us. Well,
big difference for us. Well,
that is good to hear. And about
that is good to hear. And about
3.5 minutes you're hopefully
3.5 minutes you're hopefully
we'll show that to you. So I'm
we'll show that to you. So I'm
excited. Thank you. So the
excited. Thank you. So the
other conversation that you
other conversation that you
can't escape these days is AI.
can't escape these days is AI.
How do you see AI changing the
How do you see AI changing the
way your users interact with
way your users interact with
data? Yeah. Good question. You
data? Yeah. Good question. You
know, we have some of the best
know, we have some of the best
data I think around, right? We
data I think around, right? We
understand our customer very
understand our customer very
well, but we're excited. I mean,
well, but we're excited. I mean,
really excited about agentic AI,
really excited about agentic AI,
conversational AI, and really
conversational AI, and really
using that with Tableau. So
using that with Tableau. So
today our dashboards are great
today our dashboards are great
at answering the question they
at answering the question they
were designed for, but what it
were designed for, but what it
doesn't do is answer the next
doesn't do is answer the next
question. Right? And there's
question. Right? And there's
always a next question and a
always a next question and a
next question. And so for
next question. And so for
example, we have great
example, we have great
dashboards that are monitoring
dashboards that are monitoring
our real time sales and stores.
our real time sales and stores.
Looking at conversion.
Looking at conversion.
Conversion might be working
Conversion might be working
well for an item. It might not
well for an item. It might not
be working well for this item.
be working well for this item.
Why is that? You know, I want
Why is that? You know, I want
to be making, you know, ask
to be making, you know, ask
that second question. Is it are
that second question. Is it are
we out of stock? Maybe this
we out of stock? Maybe this
item sold great and we in stock,
item sold great and we in stock,
but now it's not selling well
but now it's not selling well
guess what. It might not be on
guess what. It might not be on
the floor. So how can I use
the floor. So how can I use
agentic AI to, to, you know,
agentic AI to, to, you know,
help me answer those questions.
help me answer those questions.
And really, the way I think
And really, the way I think
about it is Tableau and AI
about it is Tableau and AI
together become my personal
together become my personal
data scientist right there by
data scientist right there by
my side. I want to give it a
my side. I want to give it a
name. I want to call it
name. I want to call it
something. It'll be my best
something. It'll be my best
friend, right? And help me
friend, right? And help me
really answer those questions
really answer those questions
real time. Well, hopefully. Yes.
real time. Well, hopefully. Yes.
Yeah, I agree with that. Yes.
Yeah, I agree with that. Yes.
Hopefully we can do show you
Hopefully we can do show you
that today. And I think that's
that today. And I think that's
what we all want. We a, we want
what we all want. We a, we want
to create that trusted advisor.
to create that trusted advisor.
But B under the covers. We want
But B under the covers. We want
to know that we can trust what
to know that we can trust what
that agent is telling us, which
that agent is telling us, which
is the key thing there. All
is the key thing there. All
right, so the last thing is, as
right, so the last thing is, as
I said, you've always been
I said, you've always been
wanting to help us, bring us
wanting to help us, bring us
towards the future. Maybe you
towards the future. Maybe you
can do a little future telling
can do a little future telling
three years from now. Imagine
three years from now. Imagine
coming back here in three years.
coming back here in three years.
How would you see? How would
How would you see? How would
you like, describe the way that
you like, describe the way that
Disney is using analytics three
Disney is using analytics three
years from now? Yeah, well,
years from now? Yeah, well,
great question. In my mind,
great question. In my mind,
we're not talking dashboards
we're not talking dashboards
like we talk today, right? I
like we talk today, right? I
want to be naturally conversing
want to be naturally conversing
with Tableau. I want to be, you
with Tableau. I want to be, you
know, really connected to the
know, really connected to the
systems like I talked about,
systems like I talked about,
you know, I want Tableau and AI
you know, I want Tableau and AI
to be continuously monitoring
to be continuously monitoring
my business, looking at trends,
my business, looking at trends,
looking at park traffic,
looking at park traffic,
looking at out of stocks. And I
looking at out of stocks. And I
wanted to, to really help me
wanted to, to really help me
answer that question that I
answer that question that I
hadn't thought about yet.
hadn't thought about yet.
That's right. Letting you know
That's right. Letting you know
what you didn't even know to
what you didn't even know to
ask, right? Something like that.
ask, right? Something like that.
Exactly. Well, we look forward
Exactly. Well, we look forward
to doing that with you. So
to doing that with you. So
thank you again for your
thank you again for your
partnership. Thanks for
partnership. Thanks for
embarrassing me. The stitch.
embarrassing me. The stitch.
It's really great to see you
It's really great to see you
here. Thanks so much. All right.
here. Thanks so much. All right.
Next up to show you the product,
Next up to show you the product,
someone who I think is a
someone who I think is a
perfect person to show you the
perfect person to show you the
product because he himself has
product because he himself has
been in Tableau probably longer
been in Tableau probably longer
than most people in this room.
than most people in this room.
He was an early member and huge
He was an early member and huge
fan of data and analytics,
fan of data and analytics,
specifically with Tableau
specifically with Tableau
itself. And he can tell you his
itself. And he can tell you his
story. And today he is the
story. And today he is the
Chief Data Officer at
Chief Data Officer at
Salesforce. Please welcome
Salesforce. Please welcome
Michael Andrew. All right. Boom,
Michael Andrew. All right. Boom,
everybody, I'm so excited to be
everybody, I'm so excited to be
here today to share what we're
here today to share what we're
doing with Tableau. And let me
doing with Tableau. And let me
start with this. I've been now
start with this. I've been now
using tableau for almost 20
using tableau for almost 20
years, back in 2007. Yes, I'm a
years, back in 2007. Yes, I'm a
little old. I discovered, oh my
little old. I discovered, oh my
God, I can see my data. I
God, I can see my data. I
started my career, like so many
started my career, like so many
of you as a data analyst,
of you as a data analyst,
looking at data, making charts,
looking at data, making charts,
finding those insights that
finding those insights that
could move the business forward.
could move the business forward.
And then I built a business on
And then I built a business on
tableau. I was a customer. I
tableau. I was a customer. I
paid for Tableau Server. I was
paid for Tableau Server. I was
providing analytics to some of
providing analytics to some of
the best brands in the world,
the best brands in the world,
like Nike and Google and
like Nike and Google and
Verizon. And I made sure I had
Verizon. And I made sure I had
Tableau Server. I made sure
Tableau Server. I made sure
every single analyst in my
every single analyst in my
business had what they needed,
business had what they needed,
had tableau to do this analysis.
had tableau to do this analysis.
And then when I joined
And then when I joined
Salesforce in 2019, there was
Salesforce in 2019, there was
something peculiar. They didn't
something peculiar. They didn't
have tableau. I was like,
have tableau. I was like,
what's up? Come on guys. And
what's up? Come on guys. And
believe it or not, I took about
believe it or not, I took about
40 emails, a bunch of meetings,
40 emails, a bunch of meetings,
escalation all the way to CIO.
escalation all the way to CIO.
So my data science team could
So my data science team could
get tableau. I was successful,
get tableau. I was successful,
we got tableau. That's right.
we got tableau. That's right.
We started using it to do some
We started using it to do some
real insights. And then a
real insights. And then a
little later that year,
little later that year,
Salesforce kind of wised up and
Salesforce kind of wised up and
said, well, maybe we should buy
said, well, maybe we should buy
the company. I don't know if I
the company. I don't know if I
had any influence on that, but
had any influence on that, but
I'm going to give myself a
I'm going to give myself a
little bit of credit maybe. And
little bit of credit maybe. And
what I'm really proud to say is
what I'm really proud to say is
now, more than seven years
now, more than seven years
later, as a chief data officer
later, as a chief data officer
of Salesforce, we run our
of Salesforce, we run our
business on tableau every
business on tableau every
single day. Tens of thousands
single day. Tens of thousands
of employees are logging into
of employees are logging into
tableau. They're viewing
tableau. They're viewing
dashboards. They're making
dashboards. They're making
decisions whether they're in
decisions whether they're in
product, whether they're in
product, whether they're in
sales, HR operations, everybody.
sales, HR operations, everybody.
And I would love to show you
And I would love to show you
all of our real internal data,
all of our real internal data,
but that might be a little
but that might be a little
irresponsible and not fitting
irresponsible and not fitting
our trust value as the chief
our trust value as the chief
data officer of public company.
data officer of public company.
So today we're going to show
So today we're going to show
you this story through Bolt
you this story through Bolt
Bikes, a really awesome
Bikes, a really awesome
imaginary company that sells
imaginary company that sells
awesome e-bikes to everybody so
awesome e-bikes to everybody so
that we can show you what
that we can show you what
tableau of the future looks
tableau of the future looks
like. Now to do this, please
like. Now to do this, please
give a major shout out to John
give a major shout out to John
Denby, our awesome demo driver.
Denby, our awesome demo driver.
All right. So we're looking at
All right. So we're looking at
bolt bikes and sales are going
bolt bikes and sales are going
pretty good. So here's my
pretty good. So here's my
e-commerce sales having a lot
e-commerce sales having a lot
of great acceleration, but that
of great acceleration, but that
only tells one story. I kind of
only tells one story. I kind of
want to know, not just
want to know, not just
e-commerce, the whole thing.
e-commerce, the whole thing.
Now in the past, when you want
Now in the past, when you want
to join this data, let's say
to join this data, let's say
data in one database to another
data in one database to another
database, you have to blend the
database, you have to blend the
data. What we are now
data. What we are now
announcing is something called
announcing is something called
composable data sources, where
composable data sources, where
you can take different data,
you can take different data,
different published data
different published data
sources, and make them as one
sources, and make them as one
actually do the join
actually do the join
materialize. Yeah, yeah. I know,
materialize. Yeah, yeah. I know,
excited. I'm excited too. So
excited. I'm excited too. So
look at this. So now we're
look at this. So now we're
joining our, of course, for
joining our, of course, for
some reason they had two
some reason they had two
databases that never happens in
databases that never happens in
the enterprise, right? You
the enterprise, right? You
never have data in different
never have data in different
places do you. And so we're
places do you. And so we're
taking now the web data with
taking now the web data with
the retail data all in one view,
the retail data all in one view,
all explorable. That's pretty
all explorable. That's pretty
cool. Composable data sources,
cool. Composable data sources,
everybody. My team is super
everybody. My team is super
excited. And so what can you do
excited. And so what can you do
with it? Well, now you can make
with it? Well, now you can make
super awesome tableau
super awesome tableau
dashboards like this. Beautiful.
dashboards like this. Beautiful.
You can see the whole world. So
You can see the whole world. So
I'm looking at it, I'm seeing
I'm looking at it, I'm seeing
my sales, I'm seeing things
my sales, I'm seeing things
going around, but maybe I have
going around, but maybe I have
some questions, questions about,
some questions, questions about,
well, how are we doing? How are
well, how are we doing? How are
these bikes being sold in San
these bikes being sold in San
Diego? Now, if you had to do
Diego? Now, if you had to do
this today, maybe you'd create
this today, maybe you'd create
a filter. Maybe you create a
a filter. Maybe you create a
tab. But now we are offering to
tab. But now we are offering to
all of you a genetic analytics,
all of you a genetic analytics,
right in Tableau Cloud, right
right in Tableau Cloud, right
in server. Now you can ask the
in server. Now you can ask the
agent this question. Well, what
agent this question. Well, what
was shipped in San Diego last
was shipped in San Diego last
month and what did we get? It's
month and what did we get? It's
thinking. It's thinking it's
thinking. It's thinking it's
coming. It's computing. Boom.
coming. It's computing. Boom.
We can see that San Diego is
We can see that San Diego is
the most popular for e-bikes.
the most popular for e-bikes.
Yeah. Shredding some of the
Yeah. Shredding some of the
trails around. And all of this
trails around. And all of this
is grounded with more than 95%
is grounded with more than 95%
accuracy. Because I don't know
accuracy. Because I don't know
about you, we've had some vibe
about you, we've had some vibe
coded dashboards showing up
coded dashboards showing up
around Salesforce and they're
around Salesforce and they're
basically totally wrong,
basically totally wrong,
beautiful, but completely
beautiful, but completely
inaccurate. So I really care
inaccurate. So I really care
about making it accurate. And
about making it accurate. And
you can see all of this is
you can see all of this is
sourced on that data. But how
sourced on that data. But how
are we getting to that answer?
are we getting to that answer?
How are we enabling these
How are we enabling these
agentic analytics behind the
agentic analytics behind the
scenes? We are offering to all
scenes? We are offering to all
of you a analytical knowledge
of you a analytical knowledge
graph. This connects to all
graph. This connects to all
your data. It understands it,
your data. It understands it,
the semantics, the maps. Don't
the semantics, the maps. Don't
worry, you don't have to build
worry, you don't have to build
this. We're building this for
this. We're building this for
you automatically. Now you can
you automatically. Now you can
modify it, you can tune it. It
modify it, you can tune it. It
will keep learning and you can
will keep learning and you can
adjust it. You can feed the
adjust it. You can feed the
intelligence. And it's this
intelligence. And it's this
grounding in the knowledge
grounding in the knowledge
graph that gives the context.
graph that gives the context.
So you can trust the agentic
So you can trust the agentic
analytics. Amazing. I can't
analytics. Amazing. I can't
wait to see all of you use this.
wait to see all of you use this.
Now, why don't we switch over
Now, why don't we switch over
to Tableau Thnks and let's talk
to Tableau Thnks and let's talk
about a semantic model.
about a semantic model.
Semantic models. Well, amazing.
Semantic models. Well, amazing.
Maybe sometimes are a little
Maybe sometimes are a little
tedious to build. So we're
tedious to build. So we're
offering you new tools to speed
offering you new tools to speed
up your semantic models. Call
up your semantic models. Call
it AI to build your AI where it
it AI to build your AI where it
can suggest fields. It'll check
can suggest fields. It'll check
if you have conflicts. We have
if you have conflicts. We have
our little Einstein magic kind
our little Einstein magic kind
of wizard, and here we go,
of wizard, and here we go,
optimize the model. So all of
optimize the model. So all of
this again, is to help you more
this again, is to help you more
quickly get to putting your
quickly get to putting your
intelligence to describe your
intelligence to describe your
data, to model your data so
data, to model your data so
that you can ultimately power
that you can ultimately power
trusted analytics. And why do
trusted analytics. And why do
you want to do this? So you can
you want to do this? So you can
put agentic analytics in the
put agentic analytics in the
flow of work. So why don't we
flow of work. So why don't we
switch over? And here we are in
switch over? And here we are in
Slack. And here's Jennifer, our
Slack. And here's Jennifer, our
awesome CEO of Bolt Bikes, and
awesome CEO of Bolt Bikes, and
she wants to know some
she wants to know some
questions. Right? Well, what's
questions. Right? Well, what's
really happening? How what are
really happening? How what are
the top bike models doing? And
the top bike models doing? And
right there in Slack, she can
right there in Slack, she can
ask the question. It's going to
ask the question. It's going to
think it's going to again, use
think it's going to again, use
that same trusted knowledge
that same trusted knowledge
graph the trusted data to be
graph the trusted data to be
able to pull it up, get an
able to pull it up, get an
answer, and there you go. So
answer, and there you go. So
electric bikes are crushing it.
electric bikes are crushing it.
Mountain bikes doing okay, I
Mountain bikes doing okay, I
think. But look at that. You
think. But look at that. You
also have a recommendation. And
also have a recommendation. And
what's unique about this is it
what's unique about this is it
brings the insights and
brings the insights and
conversations your teams are
conversations your teams are
having with the intelligence,
having with the intelligence,
but you don't just want the one
but you don't just want the one
answer. You want to be able to
answer. You want to be able to
take that intelligence and turn
take that intelligence and turn
it into action, turn it into
it into action, turn it into
recommendation, begin to make a
recommendation, begin to make a
decision, and then you can
decision, and then you can
produce this, your report
produce this, your report
automatically right there again,
automatically right there again,
grounded in the trusted data,
grounded in the trusted data,
having the key insights and
having the key insights and
having strategic
having strategic
recommendations right in the
recommendations right in the
flow of work, all of this. So
flow of work, all of this. So
again, you pick your data, you
again, you pick your data, you
connect it, the graph builds it,
connect it, the graph builds it,
and here we go. So what did we
and here we go. So what did we
just show you? We just showed
just show you? We just showed
you a lot. So we're going to go
you a lot. So we're going to go
to the slides now. And let's
to the slides now. And let's
recap. We showed you a few
recap. We showed you a few
things. We showed you the
things. We showed you the
composable data sources which
composable data sources which
enable you to now bridge all of
enable you to now bridge all of
your data into one data model
your data into one data model
you can work with. We showed
you can work with. We showed
you the conversational
you the conversational
analytics in cloud in server.
analytics in cloud in server.
Coming to desktop, we showed
Coming to desktop, we showed
you the automatic analytics
you the automatic analytics
knowledge graph that
knowledge graph that
understands your data maps,
understands your data maps,
builds it, and we showed you
builds it, and we showed you
how you could bring all of that
how you could bring all of that
into Slack. So all of this is
into Slack. So all of this is
to ensure that all of you can
to ensure that all of you can
keep having your data grounded
keep having your data grounded
in the trust and knowledge you
in the trust and knowledge you
do every day, but empower that
do every day, but empower that
AI driven agentic analytics
AI driven agentic analytics
with 95% accuracy. And I'll
with 95% accuracy. And I'll
just say a personal story, this
just say a personal story, this
is literally what we're worried
is literally what we're worried
about. Salesforce we have those
about. Salesforce we have those
dashboards, we have a few maybe
dashboards, we have a few maybe
sales leaders kind of excited,
sales leaders kind of excited,
like, oh my God, if I coded
like, oh my God, if I coded
this thing and we look at it
this thing and we look at it
and we go, yeah, but every
and we go, yeah, but every
metric is wrong, right? And
metric is wrong, right? And
that's the danger. If you just
that's the danger. If you just
kind of use AI itself without
kind of use AI itself without
this grounding, you're going to
this grounding, you're going to
get hallucination, you're going
get hallucination, you're going
to get security, you're going
to get security, you're going
to get gaps. We want to make
to get gaps. We want to make
sure that all of you and all
sure that all of you and all
the work you and the Datafam
the work you and the Datafam
put on your data can make sure
put on your data can make sure
that your company runs and has
that your company runs and has
trusted decisions. So we just
trusted decisions. So we just
showed you how you can become
showed you how you can become
the architect, the knowledge of
the architect, the knowledge of
your company, and Rick is going
your company, and Rick is going
to come up and show you power
to come up and show you power
decisions. But first, we want
decisions. But first, we want
to cut to a film from Engine,
to cut to a film from Engine,
one of our great customers, of
one of our great customers, of
how they're using tableau to
how they're using tableau to
succeed. So let's take a look.
succeed. So let's take a look.
Role of analytics is like,
Role of analytics is like,
what's the role of food and
what's the role of food and
water? It's incredibly
water? It's incredibly
important. Over 3000 businesses,
important. Over 3000 businesses,
over a million travelers are on
over a million travelers are on
the platform now. Engine is a
the platform now. Engine is a
modern travel and spend
modern travel and spend
management platform. It's a
management platform. It's a
very big space ripe for
very big space ripe for
disruption. Things come
disruption. Things come
together not in weeks, months,
together not in weeks, months,
years. Things come together in
years. Things come together in
minutes, hours, days, and we
minutes, hours, days, and we
were all doing the best we
were all doing the best we
could with the tools and
could with the tools and
resources we had available to
resources we had available to
us at the time, there was only
us at the time, there was only
so far you could go with that.
so far you could go with that.
Salesforce is the operating
Salesforce is the operating
system that makes it seamless.
system that makes it seamless.
It's the platform that the
It's the platform that the
world runs on. Agentic
world runs on. Agentic
analytics and Tableau changed
analytics and Tableau changed
the way that we think about
the way that we think about
data. It's not just for my team,
data. It's not just for my team,
it's for the whole company.
it's for the whole company.
Without it, there would be
Without it, there would be
different silos. We wouldn't be
different silos. We wouldn't be
unified. AI is only as powerful
unified. AI is only as powerful
as the systems that you connect
as the systems that you connect
it to. With natural language.
it to. With natural language.
I'm able to tell it how I want
I'm able to tell it how I want
to join some tables, and also
to join some tables, and also
it builds a semantic model for
it builds a semantic model for
me that I can then deploy, then
me that I can then deploy, then
have another agent go and
have another agent go and
analyze data without me having
analyze data without me having
to do anything other than type
to do anything other than type
some sentences. It's the
some sentences. It's the
ability to interact with data
ability to interact with data
in ways that were otherwise not
in ways that were otherwise not
possible. It changed everything.
possible. It changed everything.
CST goes up. Costs to deliver
CST goes up. Costs to deliver
go down. Customers are happier.
go down. Customers are happier.
We're getting them answers
We're getting them answers
faster. What's the trade off?
faster. What's the trade off?
There's no trade off like. And
There's no trade off like. And
now is essentially an extension
now is essentially an extension
of them. Slack to us is more
of them. Slack to us is more
like an operating system. I'm
like an operating system. I'm
able to talk to Slackbot and
able to talk to Slackbot and
get all of these details ready
get all of these details ready
for me, so that I have them in
for me, so that I have them in
front of me, having that
front of me, having that
information available to all in
information available to all in
Slack right then and there at
Slack right then and there at
your fingertips gives us the
your fingertips gives us the
ability to iterate that much
ability to iterate that much
faster. I can interact with our
faster. I can interact with our
analytics agent right from my
analytics agent right from my
phone like, hey, what's going
phone like, hey, what's going
with this? This looks funky.
with this? This looks funky.
Like, tell me what the deal is
Like, tell me what the deal is
here. I can dive into the data
here. I can dive into the data
and give me some insights, have
and give me some insights, have
data to inform the direction
data to inform the direction
you build, and then have data
you build, and then have data
after you build to inform your
after you build to inform your
iterations to inform if you
iterations to inform if you
made the right bets, it's going
made the right bets, it's going
to be revolutionary. It's going
to be revolutionary. It's going
to be game changing. We're
to be game changing. We're
going from the dumb software
going from the dumb software
era to the smart software era.
era to the smart software era.
That's literally what's
That's literally what's
happening in real time. It's an
happening in real time. It's an
incredible opportunity for all
incredible opportunity for all
these businesses. If you run on
these businesses. If you run on
Salesforce and Tableau, you're
Salesforce and Tableau, you're
nuts. If you don't. Thank you.
nuts. If you don't. Thank you.
That was an incredible story.
That was an incredible story.
So many companies, so many
So many companies, so many
organizations like Engine have
organizations like Engine have
been using tableau to power
been using tableau to power
their day to day. We spent the
their day to day. We spent the
last 10 to 15 minutes talking
last 10 to 15 minutes talking
about architecting knowledge
about architecting knowledge
that is critical. That is the
that is critical. That is the
foundation for AI. Great. Now
foundation for AI. Great. Now
how do we take that knowledge?
how do we take that knowledge?
How do you take your data? How
How do you take your data? How
do you take your semantics,
do you take your semantics,
your context and actually power
your context and actually power
decisions? And that's what I'm
decisions? And that's what I'm
going to show you in this next
going to show you in this next
chapter. But hello, Datafam,
chapter. But hello, Datafam,
this is Rekha. And in my role,
this is Rekha. And in my role,
I get to be in a lot of
I get to be in a lot of
meetings where big decisions
meetings where big decisions
happen. You know, what's the
happen. You know, what's the
catch? Unfortunately, with
catch? Unfortunately, with
access to all the AI tools, all
access to all the AI tools, all
the reports, all the dashboards,
the reports, all the dashboards,
the whole decision making
the whole decision making
process itself is slower, it's
process itself is slower, it's
harder, and it's more
harder, and it's more
disconnected than it needs to
disconnected than it needs to
be. I'm sure we all know a
be. I'm sure we all know a
better way to do this, right?
better way to do this, right?
To do that, let's zoom out for
To do that, let's zoom out for
a second. Like I said, all of
a second. Like I said, all of
us have access to all your
us have access to all your
tools, your slack, your teams,
tools, your slack, your teams,
OpenAI, ChatGPT, you name it,
OpenAI, ChatGPT, you name it,
you have it. You all have a
you have it. You all have a
question. What do you do? Go to
question. What do you do? Go to
that. Ask a question. The
that. Ask a question. The
problem every time you ask the
problem every time you ask the
same question, you get a wrong
same question, you get a wrong
answer or a different answer
answer or a different answer
from any one of these tools.
from any one of these tools.
99.9% of the time. Same
99.9% of the time. Same
question, different answer
question, different answer
across the tools. That's the
across the tools. That's the
problem. The problem right now
problem. The problem right now
is not about just getting
is not about just getting
access to your data. It's also
access to your data. It's also
not about getting the answers.
not about getting the answers.
It's about getting the right
It's about getting the right
answers at every single time.
answers at every single time.
Now, is it all of us? Are we
Now, is it all of us? Are we
going to go back and check
going to go back and check
every single tool to find the
every single tool to find the
right answer? Do you have the
right answer? Do you have the
time to do it? I doubt it, so
time to do it? I doubt it, so
there must be a better way. And
there must be a better way. And
that's why we have Tableau.
that's why we have Tableau.
What tableau does is we are
What tableau does is we are
able to build models based on
able to build models based on
your data. It's your trusted
your data. It's your trusted
knowledge, your data. Now,
knowledge, your data. Now,
composability and extensibility
composability and extensibility
have always been in our DNA
have always been in our DNA
from the day we started tableau.
from the day we started tableau.
And if you were to break down
And if you were to break down
those jargon words, what it
those jargon words, what it
actually means is you can use
actually means is you can use
tableau to power every surface,
tableau to power every surface,
every agent, and every workflow
every agent, and every workflow
based on your trusted knowledge.
based on your trusted knowledge.
That is our knowledge engine in
That is our knowledge engine in
action. And that is an absolute
action. And that is an absolute
game changer and one that gives
game changer and one that gives
up a productivity in extreme
up a productivity in extreme
ways. And that also reimagines
ways. And that also reimagines
our decision making right now.
our decision making right now.
Think about it. You're working
Think about it. You're working
wherever you are, and you're
wherever you are, and you're
able to pull up your insights
able to pull up your insights
and you're able to take action
and you're able to take action
right there. No toggling, no
right there. No toggling, no
going back and forth. And all
going back and forth. And all
of those answers are correct
of those answers are correct
and accurate because it's based
and accurate because it's based
on our data, your data. So
on our data, your data. So
here's the fun part. We took
here's the fun part. We took
all of this powerful knowledge
all of this powerful knowledge
and put it in the hands of all
and put it in the hands of all
of you. What do you all do? You
of you. What do you all do? You
create magic. You go beyond
create magic. You go beyond
creating dashboards and you
creating dashboards and you
create magic. With this, you
create magic. With this, you
reinvent new ways of working on
reinvent new ways of working on
how we do, how we operate. The
how we do, how we operate. The
best part of tableau, and I've
best part of tableau, and I've
said this every time on every
said this every time on every
stage or every one on one
stage or every one on one
meeting I've had is Datafam.
meeting I've had is Datafam.
You're so central, you're so
You're so central, you're so
critical to our strategy. And
critical to our strategy. And
that's how we do it. That's our
that's how we do it. That's our
secret sauce and that's how we
secret sauce and that's how we
operate. So I'm really excited
operate. So I'm really excited
to show you our new Datafam AI
to show you our new Datafam AI
and analytics showcase. This is
and analytics showcase. This is
where your every project, your
where your every project, your
every breakthrough, your every
every breakthrough, your every
big, bold idea that you've all
big, bold idea that you've all
created is on stage. So go
created is on stage. So go
ahead, scan, get inspired by
ahead, scan, get inspired by
that QR code and that page that
that QR code and that page that
we've built, because you never
we've built, because you never
know, one of your big projects
know, one of your big projects
can be on this very stage at
can be on this very stage at
the keynote next year. And
the keynote next year. And
that's our promise to you. So
that's our promise to you. So
speaking about incredible AI
speaking about incredible AI
showcase, I have the distinct
showcase, I have the distinct
pleasure of welcoming an
pleasure of welcoming an
incredible visionary from the
incredible visionary from the
community who has done some
community who has done some
amazing things to do that.
amazing things to do that.
Please welcome Will Sutton on
Please welcome Will Sutton on
stage. Hi, Will, so excited to
stage. Hi, Will, so excited to
have you here. Thank you for
have you here. Thank you for
joining us. Thank you for
joining us. Thank you for
having me. Okay. A little
having me. Okay. A little
birdie told me you were a past
birdie told me you were a past
champion. So what's changed
champion. So what's changed
since then? I kind of feel that
since then? I kind of feel that
everything's changing, but also
everything's changing, but also
nothing is changing at the same
nothing is changing at the same
time. I started using tableau
time. I started using tableau
in 2013 and I didn't really
in 2013 and I didn't really
know what I was doing, but it
know what I was doing, but it
was thanks to the folks here.
was thanks to the folks here.
Tableau community gave me the
Tableau community gave me the
skills and knowledge to go and
skills and knowledge to go and
take on that contest. I stepped
take on that contest. I stepped
away after that contest. I
away after that contest. I
thought, well, this is it. My
thought, well, this is it. My
career is set. You know, I've
career is set. You know, I've
got a long, happy life.
got a long, happy life.
Building dashboards. Yeah. How
Building dashboards. Yeah. How
long was I the next year.
long was I the next year.
ChatGPT was out. Huge buzz in
ChatGPT was out. Huge buzz in
the market about that. But it
the market about that. But it
hasn't stopped. And I feel even
hasn't stopped. And I feel even
now, like every week, every day,
now, like every week, every day,
there's something new coming
there's something new coming
out and I see a lot of change
out and I see a lot of change
happening there. I still come
happening there. I still come
back to this group here.
back to this group here.
They're the people that give me
They're the people that give me
the the grounding to say, what
the the grounding to say, what
skills do I need? What things
skills do I need? What things
are actually going to shift the
are actually going to shift the
dials, what my clients need to
dials, what my clients need to
know about this stuff. These
know about this stuff. These
are the people that help me
are the people that help me
stay on top of this. Oh, wow.
stay on top of this. Oh, wow.
So a lot has changed. Also, not
So a lot has changed. Also, not
a lot has changed. That's cool.
a lot has changed. That's cool.
You also built the Tableau MCP
You also built the Tableau MCP
on LinkedIn. You were the first
on LinkedIn. You were the first
one to do that. What drove you
one to do that. What drove you
to do that? Do you do that?
to do that? Do you do that?
Yeah. So I was part of this
Yeah. So I was part of this
project. I think it was a lot
project. I think it was a lot
of curiosity of like, what
of curiosity of like, what
would happen if you took the
would happen if you took the
tableau environment and just
tableau environment and just
connected it up to AI? And I
connected it up to AI? And I
want to give a shout out to Joe
want to give a shout out to Joe
Constantino on the tableau side,
Constantino on the tableau side,
who. Yeah, Joe. Joe put
who. Yeah, Joe. Joe put
together the initiative to
together the initiative to
bring together tableau
bring together tableau
developers and community
developers and community
developers working on this
developers working on this
project. It's really exciting.
project. It's really exciting.
A lot of like testing things
A lot of like testing things
out. And we landed on chat with
out. And we landed on chat with
the data source, which is just,
the data source, which is just,
again, it feeds into curiosity.
again, it feeds into curiosity.
We always want to know a bit
We always want to know a bit
more of a data source. And so
more of a data source. And so
having another way to do that
having another way to do that
with a chat bot is really
with a chat bot is really
helpful. Now this has become a
helpful. Now this has become a
staple of the tableau MCP
staple of the tableau MCP
server. It has. Thank you for
server. It has. Thank you for
doing that for us. And it's so
doing that for us. And it's so
powerful to watch that in
powerful to watch that in
action too. We are all really
action too. We are all really
excited about AI analytics and
excited about AI analytics and
all things tableau. What are
all things tableau. What are
you most excited about? Yeah,
you most excited about? Yeah,
I've got a lot of excitement
I've got a lot of excitement
for the future, but one thing
for the future, but one thing
that's been burning away from
that's been burning away from
me is vibe coding with tableau.
me is vibe coding with tableau.
Oh yes. Now I love creating
Oh yes. Now I love creating
charts in tableau. I find a lot
charts in tableau. I find a lot
of joy in that. But one thing I
of joy in that. But one thing I
don't love is I don't like
don't love is I don't like
recreating charts in tableau.
recreating charts in tableau.
If you've ever had to migrate
If you've ever had to migrate
from a different tool to
from a different tool to
tableau, there's no fun in that.
tableau, there's no fun in that.
There's no creativity, there's
There's no creativity, there's
no joy. So I feel that's a
no joy. So I feel that's a
really good opportunity for an
really good opportunity for an
AI to come and help accelerate
AI to come and help accelerate
that process. Yes, that sounds
that process. Yes, that sounds
fun. Speaking of that, can I
fun. Speaking of that, can I
show you a few things? Oh my
show you a few things? Oh my
gosh, yes. Do we want to see
gosh, yes. Do we want to see
that? Yes. Please take it away.
that? Yes. Please take it away.
Will. Hey folks, I'm will I
Will. Hey folks, I'm will I
work as a consultant at the
work as a consultant at the
information lab? I lead on AI
information lab? I lead on AI
implementations and
implementations and
environments for our clients.
environments for our clients.
Recently, I stepped into a new
Recently, I stepped into a new
role and it wasn't what I was
role and it wasn't what I was
expecting it to be. It's been
expecting it to be. It's been
long hours. I've had people
long hours. I've had people
screaming at me day and night,
screaming at me day and night,
and you just see some of the
and you just see some of the
crap I have to deal with.
crap I have to deal with.
That's right. I became a parent.
That's right. I became a parent.
Oh, boy. Oh boy, I, I find
Oh, boy. Oh boy, I, I find
myself forever on the go
myself forever on the go
nowadays. There's never enough
nowadays. There's never enough
time in my day. And so anything
time in my day. And so anything
that makes me a bit more
that makes me a bit more
productive is a big win for me.
productive is a big win for me.
I've come on a boat, bikes. I'm
I've come on a boat, bikes. I'm
here as an analyst helping
here as an analyst helping
build out their retail
build out their retail
inventory dashboard in Tableau
inventory dashboard in Tableau
Desktop. There we go. There's
Desktop. There we go. There's
my viz. It's coming together.
my viz. It's coming together.
I'm really pleased about this.
I'm really pleased about this.
I got this together and I've
I got this together and I've
had one more request come in
had one more request come in
from the CEO, no less. They
from the CEO, no less. They
came over to me, they on the
came over to me, they on the
desk, and they were really
desk, and they were really
excited. And they started
excited. And they started
drawing out this viz that they
drawing out this viz that they
wanted me to build. I was like,
wanted me to build. I was like,
I kind of like, yeah, it was
I kind of like, yeah, it was
looking like this. And I think,
looking like this. And I think,
oh, that's a, that's a double
oh, that's a, that's a double
chord chart right there. That's,
chord chart right there. That's,
that's going to be some calcs.
that's going to be some calcs.
The trigonometry alone is
The trigonometry alone is
making my head hurt. And I
making my head hurt. And I
think, well, I love the
think, well, I love the
enthusiasm. I don't want that
enthusiasm. I don't want that
to go away. But, you know, I
to go away. But, you know, I
don't think I have enough time
don't think I have enough time
for this. But I know someone
for this. But I know someone
who does my mate Claude. So
who does my mate Claude. So
here I am in Claude. I'm going
here I am in Claude. I'm going
to go and pass over this sketch
to go and pass over this sketch
over to Claude, and I'm going
over to Claude, and I'm going
to ask it now, can you go and
to ask it now, can you go and
make me make this viz come to
make me make this viz come to
life? So what will happen here
life? So what will happen here
is we'll start building out a
is we'll start building out a
tableau viz extension with VP
tableau viz extension with VP
code Williams-Sonoma, Inc. What
code Williams-Sonoma, Inc. What
this will do. So Tableau viz
this will do. So Tableau viz
extension. Really good for
extension. Really good for
these more complicated visits
these more complicated visits
that you just want to see how
that you just want to see how
it looks. So this is really fun
it looks. So this is really fun
way of actually just getting an
way of actually just getting an
idea of what that prototype is
idea of what that prototype is
going to look like without
going to look like without
having to do the heavy lifting.
having to do the heavy lifting.
And yeah, I come back like
And yeah, I come back like
later and here we go. We've got
later and here we go. We've got
a viz. I've been dragging and
a viz. I've been dragging and
dropping this in tableau. So
dropping this in tableau. So
the AI here has done a lot of
the AI here has done a lot of
the heavy lifting for me, and
the heavy lifting for me, and
I've now got that viz ready for
I've now got that viz ready for
us. Okay. Because I've saved so
us. Okay. Because I've saved so
much time building this viz out.
much time building this viz out.
Let's go and get this published,
Let's go and get this published,
you know, let's go and see what
you know, let's go and see what
the stakeholders say about this
the stakeholders say about this
viz. So to do that, I'm going
viz. So to do that, I'm going
to jump back into Claude and
to jump back into Claude and
I'm actually going to ask it,
I'm actually going to ask it,
hey, can you go and get this
hey, can you go and get this
embedded on our tableau portal
embedded on our tableau portal
for our retail partners? So
for our retail partners? So
Claude's going to work away.
Claude's going to work away.
It's not just it's going to go
It's not just it's going to go
and write the embed code for us
and write the embed code for us
and also go and get this
and also go and get this
published on our tableau site
published on our tableau site
for me as well. So this is a
for me as well. So this is a
real nice competitive advantage
real nice competitive advantage
for our retail partners. Now
for our retail partners. Now
they have the data right where
they have the data right where
they need it, right on the shop
they need it, right on the shop
floor. And they can go and
floor. And they can go and
interact with this data,
interact with this data,
answering the questions where
answering the questions where
they use their data, where they
they use their data, where they
have their analytics. Cool. Now
have their analytics. Cool. Now
we're not just, we're not just
we're not just, we're not just
shipping charts here. We're not
shipping charts here. We're not
just shipping bikes either.
just shipping bikes either.
We're also shipping the Tableau
We're also shipping the Tableau
MCP server to. So I have a
MCP server to. So I have a
follow up question from a
follow up question from a
distributor, and they can use
distributor, and they can use
the Tableau MCP server to
the Tableau MCP server to
answer that question in natural
answer that question in natural
language for them. So here I am.
language for them. So here I am.
I've connected up to Claude
I've connected up to Claude
again. What what's going to
again. What what's going to
happen here is we're going to
happen here is we're going to
connect up to Tableau MCP. It's
connect up to Tableau MCP. It's
going to find the relevant
going to find the relevant
content for this, and then it's
content for this, and then it's
going to start querying that
going to start querying that
data source to answer that
data source to answer that
user's query. This is really
user's query. This is really
powerful for me in the clients
powerful for me in the clients
I work with, we've seen so much
I work with, we've seen so much
of this being a major like win
of this being a major like win
win in these cases, because
win in these cases, because
this is saving me a lot of time.
this is saving me a lot of time.
This is would be a request that
This is would be a request that
comes into my inbox can now be
comes into my inbox can now be
handled by. This gives me a lot
handled by. This gives me a lot
of time and value back in my
of time and value back in my
day, but it also for
day, but it also for
stakeholders, they get
stakeholders, they get
immediate answers to their
immediate answers to their
questions. So here we can see a
questions. So here we can see a
full product breakdown here.
full product breakdown here.
Okay, so this has been
Okay, so this has been
conversational analytics. But
conversational analytics. But
the really nice thing about MCP
the really nice thing about MCP
is it's here in Claude. It can
is it's here in Claude. It can
be there in tableau with you as
be there in tableau with you as
well, but it doesn't just have
well, but it doesn't just have
to be tethered to a desk,
to be tethered to a desk,
that's all. Hello? Hey there
that's all. Hello? Hey there
mate. I'm your BI analyst here
mate. I'm your BI analyst here
at Bolt Bikes, ready to help
at Bolt Bikes, ready to help
you shred through some data.
you shred through some data.
What can I dig into for you
What can I dig into for you
today? How? What are my top
today? How? What are my top
selling e-bikes at the moment?
selling e-bikes at the moment?
Let me pull that for you
Let me pull that for you
properly. You top seller right
properly. You top seller right
now is commuter e-bikes with
now is commuter e-bikes with
about 19,800 units shipped in
about 19,800 units shipped in
the last 30 days, followed by
the last 30 days, followed by
lifestyle at roughly 10,500
lifestyle at roughly 10,500
units. Catch you on the next
units. Catch you on the next
wave. Thanks, dude. Could you
wave. Thanks, dude. Could you
break that down by region for
break that down by region for
me? West is absolutely crushing
me? West is absolutely crushing
it. With over 10,500 commuter
it. With over 10,500 commuter
units, while East and Central
units, while East and Central
are pulling in solid numbers to.
are pulling in solid numbers to.
Commuter bikes are dominating
Commuter bikes are dominating
every region. But West's also
every region. But West's also
got strong lifestyle sales at
got strong lifestyle sales at
nearly 6000 units. Catch you on
nearly 6000 units. Catch you on
the next wave. Thanks, bro.
the next wave. Thanks, bro.
Take care. Catch you on the
Take care. Catch you on the
next wave. Okay, there you go.
next wave. Okay, there you go.
The data. You want a hands free
The data. You want a hands free
on the go. So whether I'm in
on the go. So whether I'm in
the office, on the road, or
the office, on the road, or
back at home with the kids, I
back at home with the kids, I
can have the access to the
can have the access to the
insights and data I need. This
insights and data I need. This
has been really powerful, what
has been really powerful, what
we've seen here today. I feel
we've seen here today. I feel
the real thing you've got here
the real thing you've got here
is choice. Previously, you saw
is choice. Previously, you saw
a lot of decisions that you had
a lot of decisions that you had
to go and make manually. Now
to go and make manually. Now
you can have an automated
you can have an automated
alternative that you can run at
alternative that you can run at
scale. Here we showed you
scale. Here we showed you
embedding analytics. That's
embedding analytics. That's
where we took basically a
where we took basically a
sketch. I have a notepad full
sketch. I have a notepad full
of ideas that I now can go and
of ideas that I now can go and
pass over to an AI to see what
pass over to an AI to see what
it's going to look like, and
it's going to look like, and
get that into production within
get that into production within
minutes. Next, we went back to
minutes. Next, we went back to
Tableau SVP, where you can have
Tableau SVP, where you can have
that conversation analytics
that conversation analytics
with your AI assistant or on
with your AI assistant or on
the go. And I'm really pleased
the go. And I'm really pleased
to say that all of this stuff
to say that all of this stuff
I've shown you is available now.
I've shown you is available now.
And wherever you are on server
And wherever you are on server
cloud or next for Tableau. Now,
cloud or next for Tableau. Now,
if you've enjoyed some of this,
if you've enjoyed some of this,
I want to give a big shout out
I want to give a big shout out
to devs on stage. We've got our
to devs on stage. We've got our
hosts here, Sophia Loren here.
hosts here, Sophia Loren here.
I have had a little preview of
I have had a little preview of
what's coming up and honestly,
what's coming up and honestly,
it's really amazing, cool stuff.
it's really amazing, cool stuff.
I'm super excited for that. So
I'm super excited for that. So
do not miss that session. So
do not miss that session. So
this has been this has been
this has been this has been
powering analytics powering
powering analytics powering
decisions. What we're going to
decisions. What we're going to
do next is go and move over to
do next is go and move over to
M.k to show you identifying
M.k to show you identifying
actions. I'll see you all
actions. I'll see you all
Datafam. Thank you. Well that
Datafam. Thank you. Well that
was wasn't that amazing. All
was wasn't that amazing. All
right. I'm M.k. I'm the
right. I'm M.k. I'm the
president CTO for engineering,
president CTO for engineering,
all the engineering in
all the engineering in
Salesforce. Great to be here to
Salesforce. Great to be here to
meet you all. Now, one thing
meet you all. Now, one thing
that both Michael Andrew and,
that both Michael Andrew and,
and Bill was talking about is
and Bill was talking about is
how long they've been in the
how long they've been in the
analytics sort of business. And
analytics sort of business. And
we know the analytics business
we know the analytics business
itself has been changing from
itself has been changing from
the spreadsheet era, the data
the spreadsheet era, the data
warehouse era, the dashboard
warehouse era, the dashboard
era now to the Agentic AIRA.
era now to the Agentic AIRA.
But one thing has been constant
But one thing has been constant
through all of this that has
through all of this that has
been Tableau. We've been with
been Tableau. We've been with
you in this journey as the
you in this journey as the
analytical world changed, to
analytical world changed, to
make sure we are there for you,
make sure we are there for you,
to guide you through those
to guide you through those
changes. And this is why over
changes. And this is why over
97% of fortune 100 companies
97% of fortune 100 companies
trust and use Tableau. But it's
trust and use Tableau. But it's
not just the big companies.
not just the big companies.
Everyone from the startup SMBs
Everyone from the startup SMBs
enterprise, and everyone works
enterprise, and everyone works
and uses Tableau. Now in order
and uses Tableau. Now in order
to show some of this and how
to show some of this and how
these agentic actions are going
these agentic actions are going
to come live, let's actually
to come live, let's actually
switch to the demo. John, are
switch to the demo. John, are
you ready? All right. Now first,
you ready? All right. Now first,
this is Tableau. Next, what
this is Tableau. Next, what
you're seeing there. First, we
you're seeing there. First, we
saw Michael Andrew showcase a
saw Michael Andrew showcase a
lot of the sales demand
lot of the sales demand
forecast and so on. Let's do a
forecast and so on. Let's do a
quick inclusion of that. We're
quick inclusion of that. We're
going to pull in all the sales
going to pull in all the sales
forecasts in there. Let's
forecasts in there. Let's
upload the file there. And
upload the file there. And
you're going to quickly see the
you're going to quickly see the
sales come up pretty fast. DC
sales come up pretty fast. DC
26. There you go. That's the
26. There you go. That's the
sales demand right there. And
sales demand right there. And
voila, in a minute, you have a
voila, in a minute, you have a
dashboard that you're going to
dashboard that you're going to
see now, interesting thing.
see now, interesting thing.
What Chad also mentioned was
What Chad also mentioned was
often the sales figures are
often the sales figures are
just sales. What about the
just sales. What about the
actual warehouse inventory? And
actual warehouse inventory? And
now with the power of tableau,
now with the power of tableau,
you can bring together your
you can bring together your
sales and your warehouse. So
sales and your warehouse. So
it's no longer just your sales
it's no longer just your sales
forecasts that are showing up,
forecasts that are showing up,
but your warehouse demand as
but your warehouse demand as
well. So now you have one
well. So now you have one
operational plane on which you
operational plane on which you
can actually see everything
can actually see everything
happening from your inventory
happening from your inventory
to your sales forecast and
to your sales forecast and
everything in between. That is
everything in between. That is
your operational system. But
your operational system. But
that's not all. Often sales is
that's not all. Often sales is
a lagging indicator. When
a lagging indicator. When
somebody comes to your shop and
somebody comes to your shop and
doesn't find that route or your
doesn't find that route or your
toy, you're already kind of
toy, you're already kind of
done right. They're going to go
done right. They're going to go
to a competitor. But most often
to a competitor. But most often
all these demand forecasts are
all these demand forecasts are
stuck in unstructured documents.
stuck in unstructured documents.
It could be like this analyst
It could be like this analyst
report or other kind of things.
report or other kind of things.
And these were always separate
And these were always separate
from analytics. Not anymore.
from analytics. Not anymore.
Because today, with the power
Because today, with the power
of our agent platform in
of our agent platform in
tableau, you can simply upload
tableau, you can simply upload
these documents or even create
these documents or even create
a whole pipeline of all of
a whole pipeline of all of
these unstructured documents.
these unstructured documents.
And with that, you'll be able
And with that, you'll be able
to quickly see, as you can see
to quickly see, as you can see
here, you're going to upload
here, you're going to upload
the document. And now we have
the document. And now we have
one unified lens on which you
one unified lens on which you
have your structured data, your
have your structured data, your
unstructured data, and all of
unstructured data, and all of
them integrated. And that's how
them integrated. And that's how
you see that, in fact, that AI
you see that, in fact, that AI
is recommending and actually
is recommending and actually
telling you root cause analysis
telling you root cause analysis
right there on what happened.
right there on what happened.
You got a lot of demand on your
You got a lot of demand on your
West Coast, like we saw San
West Coast, like we saw San
Diego, but you know what?
Diego, but you know what?
Inventory is sitting someplace
Inventory is sitting someplace
else. And you can see in that
else. And you can see in that
fancy graph there as well. But
fancy graph there as well. But
because this is built on all of
because this is built on all of
those semantic and powerful
those semantic and powerful
models, we just don't have to
models, we just don't have to
see the visuals. We can
see the visuals. We can
actually open up the Tableau
actually open up the Tableau
agent right there and actually
agent right there and actually
ask the questions. John's going
ask the questions. John's going
to type now and actually ask
to type now and actually ask
the question as to, you know
the question as to, you know
what? Show me the forecast,
what? Show me the forecast,
what is going on. And this
what is going on. And this
agent is now looking at not
agent is now looking at not
just that sales data, not just
just that sales data, not just
that inventory data, but also
that inventory data, but also
all that unstructured data to
all that unstructured data to
make sure this demand forecast
make sure this demand forecast
is actually right. And so as
is actually right. And so as
you can see here, it gave you
you can see here, it gave you
actually a beautiful dashboards
actually a beautiful dashboards
as well right there embedded.
as well right there embedded.
And of course you can do it in
And of course you can do it in
all the things like in chat in
all the things like in chat in
cloud or in like ChatGPT,
cloud or in like ChatGPT,
wherever you want here. It's
wherever you want here. It's
embedded right there for you in
embedded right there for you in
that dashboard. But now this is
that dashboard. But now this is
interesting. Now I see that
interesting. Now I see that
there is a problem. Tableau is
there is a problem. Tableau is
no longer just a passive
no longer just a passive
dashboard anymore with agents.
dashboard anymore with agents.
You can now connect them to all
You can now connect them to all
the actions in your enterprise.
the actions in your enterprise.
So I can actually say, please
So I can actually say, please
move that 500 units from, you
move that 500 units from, you
know, Dallas Fort Worth to the
know, Dallas Fort Worth to the
West Coast right there. So
West Coast right there. So
you're moving from a passive
you're moving from a passive
dashboard to an active system
dashboard to an active system
right there in one pane of
right there in one pane of
glass. And you could say, okay,
glass. And you could say, okay,
you know what? I have hundreds
you know what? I have hundreds
of products. Disney probably
of products. Disney probably
has thousands of products you
has thousands of products you
can't keep like checking all
can't keep like checking all
which product, which inventory,
which product, which inventory,
what's happening all over. Can
what's happening all over. Can
we automate it? Yes, we can.
we automate it? Yes, we can.
Now you can actually use the
Now you can actually use the
same Tableau agents with all
same Tableau agents with all
the actions between with our
the actions between with our
Agentforce, you can now simply
Agentforce, you can now simply
say go to auto mode. It's going
say go to auto mode. It's going
to automatically make all of
to automatically make all of
these actions happen. And if
these actions happen. And if
you go, you can see that all
you go, you can see that all
those notifications are popping
those notifications are popping
up right there where the agent
up right there where the agent
is acting on your behalf and
is acting on your behalf and
doing it automatically. And
doing it automatically. And
soon, if you sort of fast
soon, if you sort of fast
forward a little bit, John, if
forward a little bit, John, if
you see what happens, as you
you see what happens, as you
can see here, now, you see this
can see here, now, you see this
beautiful network, it's all
beautiful network, it's all
balanced, all green because the
balanced, all green because the
agents are working on your
agents are working on your
behalf and making this move.
behalf and making this move.
Remember, these agents weren't
Remember, these agents weren't
just working on some raw data.
just working on some raw data.
We had actually created all the
We had actually created all the
semantic models. You have
semantic models. You have
created all those semantic
created all those semantic
models and made sure the agent
models and made sure the agent
had the right accurate data.
had the right accurate data.
It's not just some white coded
It's not just some white coded
dashboard that's just thinking
dashboard that's just thinking
some random data. This is real
some random data. This is real
accurate data. And also you see
accurate data. And also you see
this beautiful Sankey diagram
this beautiful Sankey diagram
below that is showing how the
below that is showing how the
distribution is working.
distribution is working.
Because these are all new
Because these are all new
charts and dashboards that we
charts and dashboards that we
have now added to tableau next.
have now added to tableau next.
All right let's switch to the
All right let's switch to the
slide. What did you see here.
slide. What did you see here.
You saw a bunch of things.
You saw a bunch of things.
Let's switch to the slide.
Let's switch to the slide.
Slide deck. What you saw is
Slide deck. What you saw is
first we were able to bring in
first we were able to bring in
data, your sales data, your
data, your sales data, your
inventory data, exactly like
inventory data, exactly like
what Chad said, which was a big
what Chad said, which was a big
gap. Now you can bring all that
gap. Now you can bring all that
together, live data. You can
together, live data. You can
also bring your unstructured
also bring your unstructured
data. So it's not just your
data. So it's not just your
structured data anymore. So you
structured data anymore. So you
can actually validate all of
can actually validate all of
your theories. And then we were
your theories. And then we were
able to create that unified
able to create that unified
model on top of it. And with
model on top of it. And with
that unified model and lens,
that unified model and lens,
you were able to convert what
you were able to convert what
was a black box, logistics and
was a black box, logistics and
shipping, all siloed into one
shipping, all siloed into one
unified operational platform.
unified operational platform.
And more than that, we were
And more than that, we were
able to then run agents to go
able to then run agents to go
analyze, automatically create
analyze, automatically create
these autonomous agents that
these autonomous agents that
can work on your behalf. And
can work on your behalf. And
finally, we wanted to make sure
finally, we wanted to make sure
it's humans and AI working
it's humans and AI working
together. So we had all those
together. So we had all those
awesome diagram charts to make
awesome diagram charts to make
sure the AI is actually working
sure the AI is actually working
right. This is the power of
right. This is the power of
agent analytics. It's not just
agent analytics. It's not just
some dashboard on the side, not
some dashboard on the side, not
just some conversational thing,
just some conversational thing,
but everything coming together
but everything coming together
into that unified plane. So you
into that unified plane. So you
can move from just passive
can move from just passive
visuals to active analytics on
visuals to active analytics on
the same control plane. All
the same control plane. All
right. With that SEIDOR, do you
right. With that SEIDOR, do you
think we can go even bigger?
think we can go even bigger?
There's one more thing. All
There's one more thing. All
right, let's see what that is.
right, let's see what that is.
All right, all right, all right.
All right, all right, all right.
One more thing and then we'll
One more thing and then we'll
bring it home. So. I do want to
bring it home. So. I do want to
show you again one more small
show you again one more small
thing we have been cooking up.
thing we have been cooking up.
But before I do that, I want to
But before I do that, I want to
do a quick recap. So at the
do a quick recap. So at the
beginning you saw Michael
beginning you saw Michael
Andrew demonstrate
Andrew demonstrate
conversational analytics on
conversational analytics on
server and cloud and next. Yes.
server and cloud and next. Yes.
Not just next. It's in server
Not just next. It's in server
cloud. And that's not just an
cloud. And that's not just an
AI tool. It's actually grounded
AI tool. It's actually grounded
in a full knowledge graph. You
in a full knowledge graph. You
also saw that and I saw many of
also saw that and I saw many of
you taking pictures being like,
you taking pictures being like,
what's that? What's that? When
what's that? What's that? When
do I get to play with that?
do I get to play with that?
Very soon actually. It's coming
Very soon actually. It's coming
in July to cloud and server a
in July to cloud and server a
little bit in the fall. But yes,
little bit in the fall. But yes,
you'll be able to get access to
you'll be able to get access to
all of that. Now, what else did
all of that. Now, what else did
you see? Not just AI features.
you see? Not just AI features.
You saw a bunch of other things.
You saw a bunch of other things.
This is a very short list. I
This is a very short list. I
said, can you put the full list
said, can you put the full list
on the screen or like it's a
on the screen or like it's a
Keynote Baird. Well, come on,
Keynote Baird. Well, come on,
put all of it on there. We need
put all of it on there. We need
a Tableau base for that. That
a Tableau base for that. That
was earlier in the presentation.
was earlier in the presentation.
This is just a short glimpse.
This is just a short glimpse.
Everything we're doing cloud
Everything we're doing cloud
server next desktop and even
server next desktop and even
public. You see the help agent
public. You see the help agent
went to public. I don't know if
went to public. I don't know if
anyone's seen that yet already,
anyone's seen that yet already,
but we're bringing also Tableau
but we're bringing also Tableau
agents to the public as well.
agents to the public as well.
So every single one of these
So every single one of these
areas is getting invested
areas is getting invested
meeting your customers, your
meeting your customers, your
partners, yourself, where you
partners, yourself, where you
are. And that's our goal. Now,
are. And that's our goal. Now,
you heard Mark talk about our
you heard Mark talk about our
knowledge engine, our decision
knowledge engine, our decision
engine. I mentioned at the
engine. I mentioned at the
beginning of the keynote, all
beginning of the keynote, all
of us are here to help create
of us are here to help create
knowledge, turn that knowledge
knowledge, turn that knowledge
into insight, and turn that
into insight, and turn that
insight into an action via
insight into an action via
decision. That is what we're
decision. That is what we're
all really, really good at. And
all really, really good at. And
that's why there's millions of
that's why there's millions of
you leveraging Tableau to do
you leveraging Tableau to do
that. And our job is to give
that. And our job is to give
you the tools to help you do
you the tools to help you do
your job faster, better, and
your job faster, better, and
with even more passion. So
with even more passion. So
that's hopefully what we've
that's hopefully what we've
been able to impart on you
been able to impart on you
today. But there's one thing,
today. But there's one thing,
how do you control all those
how do you control all those
agents? And we just saw a bunch
agents? And we just saw a bunch
of agents in the last 20
of agents in the last 20
minutes. How do you control
minutes. How do you control
them all? So we have this idea.
them all? So we have this idea.
It's called a Agentic analytics
It's called a Agentic analytics
command center. So we're going
command center. So we're going
to show you a demo. And I'm
to show you a demo. And I'm
going to be really clear. This
going to be really clear. This
is a vision demo. None of this
is a vision demo. None of this
is baked. All right. Literally
is baked. All right. Literally
created in the last couple of
created in the last couple of
weeks. It's our idea. It's our
weeks. It's our idea. It's our
vision. We want your feedback.
vision. We want your feedback.
Share it. Tell us how you think.
Share it. Tell us how you think.
Slack me Slack. Mark actually
Slack me Slack. Mark actually
Slack the engineering team
Slack the engineering team
because they're the ones who
because they're the ones who
actually do all the work. So
actually do all the work. So
huge shout out to Sirisha and
huge shout out to Sirisha and
his team for everybody else.
his team for everybody else.
All the work you do. They
All the work you do. They
should be getting all the
should be getting all the
credit, right? So let's jump
credit, right? So let's jump
into the demo. So imagine this.
into the demo. So imagine this.
You have a lot of agents
You have a lot of agents
working on your behalf. When
working on your behalf. When
you log in, what's your home
you log in, what's your home
page? You actually get a home
page? You actually get a home
page looks like this. It tells
page looks like this. It tells
you how your agents are
you how your agents are
performing. It gives you some
performing. It gives you some
to do's. I'll get back to that.
to do's. I'll get back to that.
It tells me where work is being
It tells me where work is being
done, both in production and
done, both in production and
development. Often we get a lot
development. Often we get a lot
of things kind of in that
of things kind of in that
development stage that, you
development stage that, you
know, the incubation stage,
know, the incubation stage,
other things that are actually
other things that are actually
being utilized. And I
being utilized. And I
Simplyhealth monitor, let's
Simplyhealth monitor, let's
open up that monitor. Let's
open up that monitor. Let's
take a look at that. So what I
take a look at that. So what I
see here is a view of all of my
see here is a view of all of my
agents, but not just a
agents, but not just a
conversational agent. Maybe
conversational agent. Maybe
they are metrics agents, ones
they are metrics agents, ones
alerting agents, maybe they're
alerting agents, maybe they're
data pipeline agents, all of
data pipeline agents, all of
them I get at, and what we're
them I get at, and what we're
giving you is a view and how to
giving you is a view and how to
establish performance of them.
establish performance of them.
Efficacy. That means is it
Efficacy. That means is it
doing the job it was intended
doing the job it was intended
to do? Thumbs up, thumbs down
to do? Thumbs up, thumbs down
any of those type of things.
any of those type of things.
Adoption and trust. Are people
Adoption and trust. Are people
actually believing what they
actually believing what they
say and are they having not
say and are they having not
great conversations? Are they
great conversations? Are they
coming back after they use it?
coming back after they use it?
And lastly, perhaps most
And lastly, perhaps most
importantly, data integrity.
importantly, data integrity.
The data underneath is not
The data underneath is not
right. Then no agent can be
right. Then no agent can be
trusted. So this is a view.
trusted. So this is a view.
We're monitoring all of those
We're monitoring all of those
agents and everything. In fact,
agents and everything. In fact,
you scroll down, you can see on
you scroll down, you can see on
red and yellow. And I know my
red and yellow. And I know my
agents in production. I can see
agents in production. I can see
the sessions. How many people
the sessions. How many people
are logging in, the health of
are logging in, the health of
all of them. All of that is
all of them. All of that is
here. It's a nice, beautiful
here. It's a nice, beautiful
one point view. It's a lot for
one point view. It's a lot for
me to digest. Even me even
me to digest. Even me even
stitch can't digest all of that
stitch can't digest all of that
in one second. But what if you
in one second. But what if you
could just tell me what things
could just tell me what things
I should be taking action on?
I should be taking action on?
It's right at the beginning. I
It's right at the beginning. I
have these little to do's. So
have these little to do's. So
this is the system looking
this is the system looking
behind the scenes and finding
behind the scenes and finding
out, hey, are there agents that
out, hey, are there agents that
people are using? Some people
people are using? Some people
are really engaged with it. Not
are really engaged with it. Not
enough people are using. Are
enough people are using. Are
there agents that aren't
there agents that aren't
performing well? And then it
performing well? And then it
recommends actions for me to
recommends actions for me to
take. My first one is here,
take. My first one is here,
bolt bikes. We want to make
bolt bikes. We want to make
sure that our carbon footprint
sure that our carbon footprint
is as low as you can possibly
is as low as you can possibly
make it. So we have a metric on
make it. So we have a metric on
it. A couple people are using
it. A couple people are using
it a lot, but not everyone in
it a lot, but not everyone in
the company knows about it. How
the company knows about it. How
do I get out the knowledge? So
do I get out the knowledge? So
I click on that. It gives me a
I click on that. It gives me a
suggestion. It says, hey, you
suggestion. It says, hey, you
should get these other groups
should get these other groups
to sustain. To subscribe to
to sustain. To subscribe to
this metric. I can accept the
this metric. I can accept the
suggestion and off it goes. It
suggestion and off it goes. It
sends a notification via Slack
sends a notification via Slack
and yeah, it'll it'll work in
and yeah, it'll it'll work in
teams too. Well, sir. Yeah, but
teams too. Well, sir. Yeah, but
if you want Slack, it's much
if you want Slack, it's much
better. And it'll send out the
better. And it'll send out the
notification. I don't have to
notification. I don't have to
do anything. My work is done.
do anything. My work is done.
And I've just increased the
And I've just increased the
performance of the agent
performance of the agent
because I got more people to
because I got more people to
engage. My next one is it says
engage. My next one is it says
you have an agent in, in in
you have an agent in, in in
testing. It's in my production.
testing. It's in my production.
It's not in production yet. It
It's not in production yet. It
tells me my adoption trust is
tells me my adoption trust is
good and a UAT data is good,
good and a UAT data is good,
but efficacy is not great. My
but efficacy is not great. My
thumbs down rate is 15%. That's
thumbs down rate is 15%. That's
not good enough to send a
not good enough to send a
production. I need to make it
production. I need to make it
better so I can see it against
better so I can see it against
FCB trust and it goes. But
FCB trust and it goes. But
actually, let's dive into
actually, let's dive into
lineage. Let's take a look at
lineage. Let's take a look at
what actually makes up this
what actually makes up this
agent. So what's inside of an
agent. So what's inside of an
agent? Everybody talks about
agent? Everybody talks about
agent, what's inside of an
agent, what's inside of an
agent. This is a view of
agent. This is a view of
everything in my agent. At the
everything in my agent. At the
top, I see where the agent is
top, I see where the agent is
being used. Slack. Salesforce
being used. Slack. Salesforce
Google workspace cloud. Then in
Google workspace cloud. Then in
the middle, I see the agent and
the middle, I see the agent and
I see where it's being grounded.
I see where it's being grounded.
Those are the semantic models.
Those are the semantic models.
Those are the context at the
Those are the context at the
bottom. I actually see the data
bottom. I actually see the data
that is pulling from. This is
that is pulling from. This is
one view of how my agent is
one view of how my agent is
working, and it highlights the
working, and it highlights the
area where I have some
area where I have some
challenges. So my Customer
challenges. So my Customer
Success agent, which is
Success agent, which is
allowing me to ask questions
allowing me to ask questions
about Customer Success, is
about Customer Success, is
struggling in some areas. It's
struggling in some areas. It's
struggling. And it tells me
struggling. And it tells me
across this knowledge graph,
across this knowledge graph,
all the information I'm doing,
all the information I'm doing,
what do I need help with? So
what do I need help with? So
let's jump down and show what's
let's jump down and show what's
read. Which is down below here,
read. Which is down below here,
my customer satisfaction topics.
my customer satisfaction topics.
This is a semantic model on
This is a semantic model on
customer satisfaction. If I
customer satisfaction. If I
drill in it gives me some
drill in it gives me some
suggestions. Now it's going to
suggestions. Now it's going to
come up and tell me, hey,
come up and tell me, hey,
people are confusing. The agent
people are confusing. The agent
is confusing what to use when
is confusing what to use when
you ask for customer health. It
you ask for customer health. It
should use NPS or Csat. Good
should use NPS or Csat. Good
question. We should tell it.
question. We should tell it.
Otherwise it's going to get
Otherwise it's going to get
inaccurate answers. So it
inaccurate answers. So it
actually recommends something
actually recommends something
and I can actually tell it, hey,
and I can actually tell it, hey,
this is what you should be
this is what you should be
using in that situation. This
using in that situation. This
is a perfect example of when an
is a perfect example of when an
agent will give different
agent will give different
answers, but you know how it
answers, but you know how it
should be answering. Not only
should be answering. Not only
can I accept that clarification,
can I accept that clarification,
I says, you said NPS and label
I says, you said NPS and label
them both so that they know
them both so that they know
which 1 a.m. I looking at. I
which 1 a.m. I looking at. I
also say, make sure that you're
also say, make sure that you're
using that exact same thing
using that exact same thing
across different regions. Don't
across different regions. Don't
try to mix them. So I'm going
try to mix them. So I'm going
to ask you a question. So not
to ask you a question. So not
only can it be suggestions, I
only can it be suggestions, I
can actually ask a question and
can actually ask a question and
I can ask that question, ask it
I can ask that question, ask it
to react to that and it will
to react to that and it will
give me the answers I want. All
give me the answers I want. All
right, now let's X out of here
right, now let's X out of here
and I want to go down and show
and I want to go down and show
you one last thing. And that is
you one last thing. And that is
that it's not just this agent
that it's not just this agent
that was confusing or getting
that was confusing or getting
confused between Csat and NPS.
confused between Csat and NPS.
I have an issue on my pipeline.
I have an issue on my pipeline.
I pulled data from my customer
I pulled data from my customer
health data source, and it
health data source, and it
tells me I've only refreshed
tells me I've only refreshed
this once a week. That's no
this once a week. That's no
good. I didn't know that. But
good. I didn't know that. But
it tells me that it says, hey,
it tells me that it says, hey,
do you want to do it every day?
do you want to do it every day?
So yeah, the fact I might want
So yeah, the fact I might want
to come back and actually do it
to come back and actually do it
in real time, but this is
in real time, but this is
something on behind the scenes,
something on behind the scenes,
letting me know the issues with
letting me know the issues with
how I make my agent perform
how I make my agent perform
better. So that's what we call
better. So that's what we call
a Command Center. So again,
a Command Center. So again,
this is just our thoughts. We'd
this is just our thoughts. We'd
love to get your feedback on it.
love to get your feedback on it.
Slack me send others. That is
Slack me send others. That is
how all of us can make these
how all of us can make these
agents perform better. In the
agents perform better. In the
same way that we want to make
same way that we want to make
our dashboards perform better,
our dashboards perform better,
our business, perform better,
our business, perform better,
the same concept so we can go
the same concept so we can go
back. And what I want to hope
back. And what I want to hope
all of you do go and explore
all of you do go and explore
all the sessions. Learn about
all the sessions. Learn about
how you can use AI to
how you can use AI to
accelerate our vision to help
accelerate our vision to help
people see, understand and act
people see, understand and act
on data. Learn how you can
on data. Learn how you can
build new visitors, learn how
build new visitors, learn how
you can leverage desktop and
you can leverage desktop and
all the new ways. Most of all,
all the new ways. Most of all,
get to know everybody here.
get to know everybody here.
Share your experiences. Make
Share your experiences. Make
this event really what makes it
this event really what makes it
so great. With that, I'm gonna
so great. With that, I'm gonna
turn it back over to Mark. All
turn it back over to Mark. All
right. How would show? Pretty
right. How would show? Pretty
cool. Awesome. Okay, so I was
cool. Awesome. Okay, so I was
told to go fast because we're
told to go fast because we're
running late, but. Okay, we
running late, but. Okay, we
have an amazing TC plan for you.
have an amazing TC plan for you.
We have devs on stage tomorrow
We have devs on stage tomorrow
at 9 a.m. Who's excited for
at 9 a.m. Who's excited for
that? Tomorrow we're bookending
that? Tomorrow we're bookending
the day with iron is at 4 p.m.
the day with iron is at 4 p.m.
who's excited for that? And who
who's excited for that? And who
could possibly be excited for
could possibly be excited for
data night out with Dillon
data night out with Dillon
Francis? All right. We have an
Francis? All right. We have an
amazing, amazing week here. I
amazing, amazing week here. I
will end it the same way I
will end it the same way I
ended it before, but a huge
ended it before, but a huge
thank you. This is going to be
thank you. This is going to be
a fantastic week and I only
a fantastic week and I only
have one more thing. We'll see
have one more thing. We'll see
you all here next year in San
you all here next year in San
Diego for TC 27. Thank you very
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Tableau Keynote 2026: Go from Seeing to Doing with Agentic Analytics
The DataFam and Tableau taught the world to see data. Now we're making it act-transforming trusted knowledge into automated decisions and real-time results with agentic analytics!
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