All right, let's dive
into the keynote's
biggest moments,
where the industry is
headed, and how agentic
analytics transforms
reporting what happened
to orchestrating
what happens next.
I'm joined by Tableau
superstars Ed Bure
and Bailey Ferrari and
Trevor Hall. Welcome,
guys. I'm going to
just kick us off with
a lightning round.
What was your favorite
part of the keynote?
Jump on in. I
mean, to me,
it's the
customer stories.
Disney, Engine, and
most importantly,
Salesforce, because
how we use our
product matters,
and it is incredible
with what we're doing
there. I love how
you light me rounds
with like three
sentences. I'm going
knowledge graph.
You're going knowledge
graph? Knowledge
graph. Let's do knowledge
graph. All right.
I'm going to go
with command center.
Command center. I
think it's just showing
how, you know, we
need to be, you know,
giving our customers
all the tools that they
need to be able to
see everything that
they need to be able
to manage all these
pieces. And I just
think it's, yeah, very
exciting. Yeah, that
was a big announcement.
And then there
were some oohs and
ahs as we were watching
it. Do you guys
want to say anything
about command center?
Yeah, I mean, I think
that the command center
is something that
customers have been
wanting. And there's
an appetite for really
like a single pane of
glass across all of
these different analytical
assets. Something
I'm really convicted
and passionate about
and talk to customers
really every single
day in my role and just
in general, because
I'm a dork and I like
the LinkedIn messages,
feel free to send
them to me, is the
concept of like, how
do we actually deliver
an interoperability
story? How do we actually
help you have that
unified view, not only
of Tableau assets,
but again, of the
agents that you're
building, of any kind of
other broader Salesforce
analytic solutions?
And so to have like a
unified view that has
lineage, tracking,
visual cues inside to
show you how people are
adopting what you're
seeing is incredibly
powerful. And I think
something that the
DataFam and our
customers have been asking
for for quite a while.
So I'm thrilled that
we're delivering on
that. Yeah, it's very
exciting. Now, one
of the themes was that
the DataFam's role is
evolving very quickly.
And Bailey, how is
the role changing with
agentic analytics?
Yeah, I think the
biggest thing that our
customers are going to
need to keep in mind is
that context layer.
So the agents do need
context. They're already
ahead. you said it
perfectly how we have
data in tableau they
have data oftentimes in
salesforce and in data
cloud so how do we make
sure that we infuse
the um you know published
data sources the
data sources that you're
going to build your
agents off of with
the context that it
needs and that's what
you know tooling like
knowledge graph is going
to help with tooling
like the command center
is going to help with
um and all of the great
you know agent force
observability um
components that are
showing you you know
what utterances are used
what questions what
response what's the accuracy
All of that is going
to be absolutely
critical as we start to
really try to, you know,
stand up and become
agentic enterprises.
Yeah. And, you
know, agents were
front and center
in the keynote,
along with
Stitch and Groot.
Baby Grogu had a
little cameo there.
But, Ed, what
does it actually
mean when AI does
the heavy lifting?
How do humans still
lead? I think what I
love the example with
Will Sutton, right? He
was an Iron Viz champion,
and it just feels
like his career is
almost restarting in
terms of the opportunity.
But he's able to
take advantage of all
the work he's done in
terms of just the study
of analytics. There's
a lot of work that
goes into that. And so
this agentic piece is
taking away some of
those mundane tasks.
And it's allowing him
to continue to change
the game with the
customers he's supporting.
And that's where
this is coming together.
And it's been incredibly
exciting to see. I
loved when he said
that he got to focus
on the creativity and
joy of building Viz's
because a lot of that
other work was being
handled. And I think
that's what Tableau
is all about. Like, it
truly is a platform.
I begged for this job
because I loved,
literally, creativity and
joy. It was like
the, you know, design
platform of data. And
so it blends two things
that I love so much,
data and, you know,
viz. And again, Tableau
Public, plug it. They
talked about it. So
incredibly cool. Yeah.
Trevor, in this current
landscape that we're
seeing right now,
and it seems to be
changing so quickly,
what sets Tableau apart?
I mean, I think we've
been hearing it from
this interview, from
the keynote, too, which
is the success of agents
is really about the
knowledge that they
have right and the good
news is all of that
knowledge is already
encoded in tableau you
know this is the work
that people have been
doing for the last 20
years building published
data sources dashboards
visualizations prep
flows all of that is
the semantic context
that runs your business
today and i think
really what we're seeing
is a greater democratization
of data access
to more people in an
organization and it's
all through the curation
of that knowledge.
And the good news
is I think what sets
it apart is everybody's
already been doing
that. So it's really
a foundation that
you can then leverage
with our platform
to be really
successful with all of
everything you just saw
and everything that'll
be happening in the
next year or two.
Exciting. And
Bailey, what are you
hearing from
customers? Are they
excited? Do they
feel like they have
to start over?
Are they nervous?
So I have the distinct
honor of working
almost exclusively
with tech customers.
In tech specifically,
there's an incredible
appetite for AI, for
agents, for building
this out. But again,
I think that, you
know, a lot of people
are using AI in their
day to day. I do.
Sometimes I'll use AI
for meal plans, for
workouts, low stakes,
right? When their stakes
are much, much higher
than, you know, how
many carbs I'm eating
per day, they're
hesitant. There's a
little bit of hesitancy
there of like, again,
how do I make sure
it's trusted? How do I
make sure it's
accurate? How do I make
sure that the decisions
that people are making
are consistent?
Because again, when you
ask a question and it
gives you guidance,
the same guidance
should be given to every
rep, right? If it's
the same question, it
should be similar
guidance. So I think that
there's, you know, some
hesitance there, which
is a healthy, you know,
healthy hesitance,
because it is, you
know, much higher stakes
than, you know, less
important questions. But
I think there's a true
enthusiasm as well.
Really, where we're
at right now, there's,
you know, a lot of
people in this space, the
industry is kind of
evolving, blowing up,
like people are looking
to trusted, you know,
entities, customers,
to deliver AI that's
going to actually work.
And I think Salesforce
is uniquely positioned
to do that because
of all the rich context
that we have. And
because, again, because
of the fact we can
leverage assets that
people have been building
for 20 plus years. Yeah.
And Ed, we saw Slack
in that first demo. Can
you talk to us about
how Slack helps us
work smarter in the
agentic era? Yeah. I
mean, when you think about
Slack, it is the world
that we live in every
single day, interacting
with each other,
with our peers. And
it's got 2,600 apps on
the marketplace integrate
with Slack as well.
So it's becoming the
largest AI ecosystem.
The top 50 AI companies
are using Slack to
run their business,
examples like Anthropic.
And so now when you're
using these examples
like Anthropic or
like Slackbot powered
by Anthropic to go
ahead and ask any
question that you have
in the context of the
unstructured data in
your conversations,
building out canvases
to run these motions,
but then they're
also powered by the
semantic models that
Tableau Next has been
built on, it becomes
incredibly powerful
of this one plus
one equals three
and where we're
going with Slack is
incredibly exciting.
I can't live without
Slack and I can't
live without Tableau.
And this is where
the future is going.
Exciting stuff. All
right, Bailey, let's talk
about the skills that
the DataFam is going
to need to truly embrace
agentic analytics.
We've talked about data
curation. So how do
they start building
those skills? Yep,
absolutely. So I think
that the biggest place
that I would recommend
the DataFam start is in
Tableau and the tooling
that they already
are the most familiar
with. Again, there's the
ability to add metadata,
add descriptions
to your published data
sources as is, and
agentic capabilities in
the Tableau platform.
We heard it in the
keynote. It's not that they
have to, you know,
build agents in Tableau
next to start leveraging
AI, leveraging
agents. In Tableau Pulse,
we have tooling like
Pulse Discover. You
can ask open-ended
questions in Tableau right
now today. So really,
you can start right
now, right now with the
assets that you already
have, building some
familiarity of what
questions can I ask? Do
I like the responses?
Again, there's tooling
even in Tableau right
now where you can give
a thumbs up. Is it
accurate? Is it right?
It structures the
recommendations when you're
asking questions. So,
so much you can do
in the Tableau platform
to start getting
great agentic responses.
And then I think the
natural progression
into that is something
into the broader
Salesforce platform with
AgentForce because it
is such a robust tool,
such a robust UI to
really build and curate
the agents. So it's
a natural progression
and really crawl, walk,
run. They can start
crawling truly right
now in five minutes.
That is great advice.
And Trevor, I'm going
to come to you. What's
one thing or a few
things from the keynote
that you want the
data fam to take home
with them that they can
turn into real business
impact right away?
I think the one
thing I would
recommend for
everybody is we're in
an era where we're
all learning.
And it's our responsibility
at Tableau, we
feel, to be able to
provide all the tools
and capabilities and
APIs and MCP services
to be able to help
enable all of these
new agentic capabilities.
And so what I want
the data fam to take
away is experiment.
You know, find the
right combination of
taking, you know,
Tableau MCP and like we
saw Will do with Cloud
and be able to give
it custom skills on top
of that to orchestrate
maybe a new way to
generate business
or ask questions of
your data that's already
encoded and available
in your deployment.
And I think the
important part is you
hopefully will inherit
the trust that you've
already built with
Tableau because it's
built on our platform.
It's built with
Tableau MCP, and you're
able to leverage things
like composable data
sources and all the
other new features
that we showed today.
And I really want
to encourage this
sense of experimentation.
I think that's
where you learn
really what agentic
analytics is about,
and you learn the
tools, and those
become new tools in
your tool belt that
you've already had.
So experiment
and have fun.
Great advice. Anything
else to add on to
that? I think Will said
it really well. He did
his presentation and
then he said, and the
community's been a
huge part about it. And
I think it's important
for us. We spend the
first 10 minutes of the
keynote thanking the
community. And so
they're such a critical
part. So you experiment
with the community.
You invest in your local
Tableau user groups.
You invest in this.
The buzz behind us
is incredibly exciting.
I think that's a huge
part of it. If you
are new, if you feel
like you are on your
own, you are not, reach
out. we're here to
go ahead and help and
figure out this next
chapter, but you're making
the right bet right
now with us in this
opportunity. Yeah.
Learning from one another,
learning from the
community. Absolutely.
Thank you guys so much
for sharing these insights
with us and enjoy
the rest of the
conference. Thank you.
Thank you so much, Diane.
