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Okay.
Welcome to Release Readiness.
And this episode
because it's all about analytics.
We're bringing you
the latest innovations directly
from our product experts
in this jam
packed Summer '25 release
updates episode.
And don't forget,
we'll be taking
your questions directly
to the product teams
and broadcasting their answers
on Salesforce Plus.
So check out the description
because we've got the link
to the Q&A
form as well as the schedule
of our Q&A broadcast.
But before we start,
I'd like to remind you
to make
all purchasing decisions
based on currently
available technology.
Well, let's get started.
First up,
say goodbye to data silos
and hello to trusted,
consistent insights
with Tableau Semantics
built into Data Cloud.
Teams can now define,
connect, and reuse
unified data models,
powering smarter
visualizations across Tableau,
Next, and beyond.
Omer Sedakah,
the Product Manager, is here
to show us this use case in action.
Here it is. Thanks, Carolyn.
Today
I'll walk you through
how Tableau Semantics, our
AI powered semantic layer
integrated in Data
Cloud, helps
deliver consistent,
trusted data for analysis.
Here you can see
a list of data model
objects or DMOs in Data Cloud.
These are data views
that can also represent
external sources like Snowflake
using Data Cloud, zero copy
integrations, and more.
Semantic models serve
as a single source of truth
for data across the organization.
These models can power
various consumption layers
such as Tableau,
Next, DCR, and more.
Building a semantic
model can be done
both either in Data Cloud
or directly in Tableau Next.
In this demo,
we'll use
an existing semantic model
I've already built in Data Cloud
and connect it to Tableau
Next for analysis.
Now we're in the semantic model
authoring experience
where we can edit
the sales and service model
in the canvas.
We see the data objects
in our model.
For example, Account
TC that which holds
all of our customer's accounts
data, lines between objects
represents relationships.
These enable
flexible, context aware
joins at query time,
with no need to
physically merge tables in advance.
On the left panel,
you'll find properties
for each data object,
plus tools to define definitions
like metrics, calculated fields,
logical views, groups,
bins, and more.
You can easily adjust
field properties to improve accuracy
and presentation,
such as changing data types,
field names, or adding descriptions.
To connect data objects,
drag a line between them.
For example,
I will create a one between
the two case objects.
You can also
use logical
views to define custom
joins and unions,
like combining products
and sales objects
with an inner join
to create a purchased products
view.
A powerful part of Tableau
Semantics is model reuse
and extension of verified models.
Here I've extended the sales model
by adding service data.
You can see both in the canvas
and the left panel.
This lets teams maintain
a single source of truth
while adapting models
for specific needs.
You can also define metrics
and calculations
to track performance consistently.
For instance,
let's say
I want to identify accounts at risk.
First, I have a calculated dimension
for high priority case flag,
which marks accounts
with urgent issues.
Another calculation is time
since last purchase.
Next I'll create
a new
calculated field
called Account Revenue at Risk.
Identifying accounts
that haven't purchased
in over 300 days
and have a high priority case.
To ensure it's all
working as intended.
I can test it out.
Great.
Just as expected.
Everything is auto saved,
and I'm ready to build reports
based on it.
The semantic layer
also includes metrics.
This is a KPIs
that business users
can explore,
subscribe to,
and set goals or alerts on.
For example, here's
our sales revenue metric.
Built on sales amount and date.
I can slice it further
by region
or sales channel to better track
how my revenue is performing.
Now that the model is ready,
I can start building
visualizations
on top of this trusted,
curated data in Tableau
Next.
We'll start by creating
a new workspace.
This is where I build
my analytical scenario.
I will add my existing
semantic model,
which was built in Data Cloud,
and I would like to use
it for my analysis.
Now let's create
a visualization.
I drag the account name
to show up on the rows
and Revenue at Risk to the columns.
Clicking on the Revenue at Risk
measure allows me to filter out
zero values, and keep
only the accounts
that have revenue at risk.
All I need to do
now is save my visualization
and share it with my team.
This was an end to end
demo of Tableau Semantics
within the Tableau
Next flow of work.
Back to you, Carolyn.
Okay, now
that's truly insightful
because from data
model to dashboard,
this is an analytics
with intelligent baked right in.
And we're going to keep it going
with the new Tableau
Semantics Connector.
So get ready to analyze
smarter not harder.
Now you can instantly connect
to curated semantic models
in Data Cloud.
No manual data modeling needed.
Allan Folting,
Product Management Director,
put this together to show us.
So let's take a look.
My name is Allan Folting,
and I'm a Product Manager
at Salesforce working on Tableau.
I'm excited to
announce the new Tableau
Semantics Connector
for Tableau Desktop,
Server and Cloud
that lets you connect
to semantic models in Data Cloud
and immediately
begin analyzing and visualizing data
without having to create
data models from scratch.
So let's take a look
at how this works.
Here we have a semantic model
based on data from a bookshop.
It contains information
about books
and authors
as well
as library checkouts and ratings,
which can help us understand
more about the popularity of books
and authors.
We will go to Tableau
to take a look at this.
Now before the new Tableau
Semantics Connector,
you can already connect to tables
in Data Cloud using Tableau's
Existing Connector
that you see here.
However, in order to use that,
you need to know
which tables to bring in
and how to relate them.
That's not always easy
with the new Tableau
Semantics Connector.
There is an easier way
that enables more people to do this.
Let's take a look.
I'm going
to connect to my org,
authenticate.
And as soon as I'm done with that,
I now get presented
with a list of semantic models,
not a list of tables
which I have to figure out
how to choose from
and how to relate.
Now I can just select bookshop.
Click connect.
And I've got a whole data model
already defined in Tableau.
You'll see here that all the tables
and all the fields
are organized by their types.
And whether or not there are measures
or dimensions.
And that comes from the metadata
in the semantic model.
If I go to the data source pane,
you'll see
that the data model in Tableau
looks almost exactly
like the data model that
you saw in the beginning.
It's just shown the way that Tableau
normally presents data models
to make it easier for users to use.
They don't have to learn a new UX
or a new calculation language
to do things in Tableau.
Okay, so let's do a quick analysis.
In order to do that,
I'm going to go ahead and add sales
to this visualization.
And in order to compare sales
with popularity
I'm going to go ahead.
And add checkout
and ratings.
I'm going to change
rating to use average
as the aggregation function.
And then I'm going to go ahead
and add book titles.
Lastly, I'm
going to sort this by checkout.
So we can get a sense
for popularity.
I'm going to go to descending and
I'm going to pick the checkout
field.
All done.
Great.
So now I can get a sense for,
how sales compares to popularity.
And it's actually surprising
in this case
that some of those top books there,
and not in terms of checkouts
and high ratings,
actually don't sell that much.
So maybe there's an opportunity
for a campaign.
Let's go and create
one more of these.
In this case, I'm
going to go ahead and create a map
that shows number of checkouts
by where each author lives.
Which country.
So I'm going to go ahead
and at number of checkouts on size.
And then lastly
I'm going to throw these things
together in a dashboard.
So what I showed you here
is that with semantic models
with this new Tableau
Semantics Connector,
all you have to do is connect to one
and you can start doing analysis.
No data modeling required.
And Tableau leverages
the same semantic models
that power other applications
like Agentforce, Tableau
Next, Data Cloud reports,
and customer applications.
When you use this new connector,
Tableau sends semantic queries
to the semantic layer,
which ensures that the business
logic and data security
defined in the semantic
model is available
and applied the same way in Tableau
as in all other applications
using it. That's it for me.
Thanks so much.
All right.
That's amazing.
One click and you're exploring
trusted secure data across the org.
This changes the game
for every single Tableau user.
And we're going
to keep the coolness going
because the next
feature is analytics that talk back
with Tableau
Next and Agentforce
working together.
You can ask business questions
in plain English and get instant
AI powered insights,
complete with visualizations
and context
that you can trust.
Ankita Dutta,
Director Product Management is here
with this next one,
and I want to see it in action.
Here
I'm logged into my demo
org and I'm on my sales
performance dashboard.
I'll open Agentforce over here
and choose
Analytics Agent
because that's
what I want to use at this point.
My dashboard shows me a high level
summary of key metrics
such as open
pipe,
pipeline value, total sales, etc.
but end of quarter is coming through
and I want to see what's going on
with total sales
in the current quarter.
So I simply asked that
in natural language to my agent.
Now Tableau Next
is natively integrated
with Agentforce
and it comes with pre-built
analytics skill concierge.
This helps you unlock
conversational analytics
so I'm able to explore my
data in natural language.
And using
concierge, I can
deep dive
into this quarter's performance.
So over here
you can see my agent
came back with an answer,
and I can see whats the total sales
for the current quarter.
Now let's start diving deeper
into this insight, right.
I want to
I want my agent
to break the sales down
by product family.
So I simply ask, at this rate,
can you go ahead and break
sales down?
And Agentforce
interprets my question
by mapping it to business
concepts defined
in my semantic data model,
the underlying layer,
ensuring the context
and intent are clearly understood.
It then uses this understanding
to generate a precise query,
runs it against the data layer,
and returns a tailored response
with a visualization.
So here
I can see
it came back with an answer
and it gave me a viz
so I understand what my data is.
Now over here
I can see that
Sales Suite isn't doing that well.
But it's a strategic
priority for my company, right.
So I want to understand
what's driving down Sales Suite
total sales.
So that's exactly what I go ahead
and ask my agent, right.
And as you can see,
this tells me more from the
what is happening
to why it's happening,
unlocking the kind of
insight that drives action.
So Agentforce is thinking
again at this point,
and let's
see what it comes back with for,
with for the response.
All right.
There we go.
So here
we can see Agentforce returns
a summary to help me understand
what's driving down
Sales Suite performance.
And we have a lower conversion.
And win rate,
as we can see over here.
And even a reduction
in our weighted pipeline.
So I need to figure out
how to turn this around, right.
So I simply ask my agent
what's the pipeline coverage
per product family for this quarter.
And the agent is thinking,
going back
to my semantic layer,
mapping my question
to business semantics
and going to the data layer
to retrieve the answer.
And there we go.
It comes back
with an insight with a viz
that I can see over here.
And this is why I rely on
Tableau Next.
It presents
clear, trustworthy insights
that I can act on.
At the core
is Tableau Semantics,
integrated with Data Cloud.
It gives business
meaning to data and metadata,
allowing AI
agents to understand and respond
in the language of business.
And that's why I can ask
about total sales pipeline
or drill
into individual opportunities
the owners
and get reliable answers each time.
So that's concierge for you.
That's awesome because it
takes us from
what happened to why it happened
in just seconds.
This is next level decision making.
And up next is building amazing
content in Tableau.
Next, it's easier
and even more powerful than ever
from semantic models
and rich visualizations
to smart actions
and embedded dashboards.
It's a full end to end
creation experience
designed to turn insights
into impact.
Edward Mengel, Senior Director,
Product Management,
put this together to show us.
Let's take a peek.
Thanks, Carolyn.
In this demo,
I'll give you all the basics
you need to get started
building an app in Tableau Next.
Everything in Tableau
Next starts in the workspace.
Here I've got my workspace.
You can see I've got my dashboards,
my visualizations
and my semantic models.
It's super easy to
create new content
or even reference
existing content
outside of your workspace.
In this case,
we're
referencing this Sales
Cloud semantic model.
I've got all these
relationships defined.
Also define these metrics
to measure my business.
Once you've got your semantic model
set up,
you're ready to start
building visualizations.
Tableau
Next supports
a rich array of visualizations.
We've got bars,
lines, scatter plots, heat maps,
variations of bar, donut,
cross tabs and tables.
Let's start by editing the stacked
bar chart.
And you'll notice that the Viz
authoring experience
is very familiar.
It's super easy to make changes,
swap things around,
or even just drag
and drop to configure.
Once you've got your viz
the way you like it,
the next best thing to do
is add actionability.
So in this case, I'm
going to hit this button
to toggle the action panel.
Once that's open,
I can configure my actions.
Now in this case
I've got
the ability to select
a user.
And here I've got an open
record action
as well as some Salesforce
platform actions.
Here you can see
we've configured the action,
the opportunity ID
and the actions that are relevant
with this group,
if we want to reference an action
outside of the Salesforce platform,
that's also super easy.
We can use an open URL action.
In this case
we're going to inject
this user's name into LinkedIn
to open up their profile
on LinkedIn.
Once we've added actions
to our vizzes,
now it's time to pull
everything together.
So let's
open up this dashboard.
And in this dashboard you can see
we've got filters,
we've used some of these metrics
that we defined, visualizations,
all arranged.
When you've got everything
arranged the way you want
let's even add more actions.
So in this case
we've got our main viz here.
But I want
users to be able
to do things from here.
So when they select an opportunity
they should be able to send
a recommendation.
Agentforce is
super powerful
to add smarter
and semi-structured analysis.
So in this case,
what we're going to do is
we'll take that
highlighted opportunity
and kick off this flow.
In this flow,
we're going to get the opportunity
and make a recommendation.
Then we're going to show
that recommendation to the user
in the email editor screen.
And then the user has the option
to edit that and send the email.
We can also
do actions on
multiple records at once,
like this action over here,
which is going to update the stage
on all of the opportunities.
In this case, you'll notice
that when we configure it,
we've got a list of IDs
that we send the action.
Once you've got all your actions
configured,
the next thing to do
is embed this in the flow of work.
You can embed Tableau
Next dashboards in home pages
or record pages.
Now let's try it out.
I can select an opportunity,
I've got these types
of actions on it,
or I could just send up
a recommendation, pass it that ID.
Now this has gone
researched this, got a summary
and a recommendation.
It gives it to me right
in this text area.
I can review this, edit it
and then send that email
as I'm done.
That's
everything you need
to know about building
amazing applications with Tableau
Next. Back to you, Carolyn.
Thank you. Ed.
I mean from drag
and drop dynamic action flows.
Tableau
Next isn't just for data,
it's for doing all right now.
Data just joined the conversation
with the new native integration
between Tableau Next and Slack.
Teams can now explore live
metrics, share insights,
and take action in channels
and canvases,
all without
leaving their flow of work.
Austin Haag, Product Management
Director, has a demo for us,
so let's take a look.
my name is Austin and I'm
a Product Manager on the Tableau
Next team.
I am so excited about our new native
integration between Tableau
Next and Slack.
We're bringing live visual insights
into the team channels and canvases,
where your team already
collaborates and takes
action together.
This will inform the team
with the latest health
of the business,
and ensure decisions
are being made based on data.
Imagine
that I'm an account
executive on our sales team.
I start my day in Slack,
and I see a message from my manager
that her metric digest
just came in
and total sales are down 32%.
She's wanting us to dig
in together to understand
what's going on.
For me to understand
what's going on with sales,
I need to also understand
what's going on
with my other metrics
that relate to it.
Thankfully, now I can in Slack.
We have a team canvas
pinned to the channel,
which shows me the latest value
of all of the metrics
that matter to me
and my team, filtered
to our team's context.
Here I can see that
total sales are down,
but so is pipegen,
and I can see how it relates
to other metrics
like conversion
rate and our sales cycle.
It looks like
this is a nuanced story,
so I want to talk about it
with my team tomorrow morning.
I'm going to share it
into the team channel,
Sales Leads. Hey team,
let's discuss
how to bring sales back up
in tomorrow's call.
When I share this metric
Tableau Next is logging in
on my behalf,
loading the latest data,
and sharing a snapshot to the team
so everyone can access it
and rally around it together.
This is just like
if I shared a screenshot,
but there's so much more.
From this latest value,
I can also always access the up
to date information,
and I can see so much more of this
going on across the business.
For example,
in this case
I'm looking at related threads.
These are all of the mentions
of this metric across departments.
As a salesperson, sometimes I
don't really understand
what's going on upstream
and downstream of me.
Now I can.
I see there's a conversation
happening about total sales
in our marketing channel.
My marketing team member, Matt, said
that there's been great work
on a manufacturing campaign.
It's now the third largest industry
in the past 30 days,
and it might increase total sales.
Let's click
this related conversation
to open the marketing
campaigns channel
where it's happening.
Now I can jump in and continue
this thread.
Wow.
It looks like manufacturing
is up over 100%
compared to the prior period.
And the team is discussing
creating a similar campaign
for the Transport vertical.
This is super important
for me
to understand,
to inform which opportunities
I should focus on coming up next.
In addition,
I can always explore
more in Tableau.
Next if I want to drill in.
I can easily
click Explore in Tableau Next
where I can access
these insights myself.
I can see that the filters
that are being discussed
are maintained.
I can apply additional filters,
break down the metric
by different dimensions, and more,
making sure that the insights
that I'm looking for to drive
the action are right
at my fingertips.
I am so excited to see how this new
native integration between Tableau
Next and Slack
transforms
how your team collaborates
around insights together.
Back to you, Carolyn.
All right.
I absolutely love this
because team chats to smart stats.
There's integration.
Turn Slack into your new command
center for data driven decisions.
And so next up we're diving into
how the Agent Analytics
app in Tableau
Next gives supervisors
the insights
they need to boost
agent performance.
Because in just a few clicks, users
can pinpoint issues
by agent, by topic or action
and then take immediate steps
to improve outcomes.
Karthik Balasubramanian,
Senior Product Manager is here.
Take a peek.
Hi everyone.
I'm Karthik,
Senior Product Manager
in the Tableau Next team.
In this demo,
I'll be showing you
how you can use the Agent
Analytics app built on Tableau
Next.
Steve works for Acme
Companies service department
as a supervisor.
Steve logs into Salesforce
and sees Agent Analytics app
built on Tableau
Next, and reviews the insights
to understand
the impact of agents
on the business outcome.
In the overview page,
Steve sees key metrics
such as agent health score,
engagement rate, escalation rate,
deflection rate, and a few other metric cards.
Higher the agent health score,
better for the business outcome.
Steve notices
a significant increase
in the escalation
rate in the past few days.
Now, Steve, wants to dig deep
and understand more
in the agent usage,
Steve sees that a different agent
is having a lot of
escalated sessions.
Now Steve goes
to agent effectiveness.
Here Steve, sees a bunch of metric
cards, charts
that explain the sessions,
topics and actions,
trend and usage breakdown,
table
that gives detailed information
for agent,
topic, action, and also sessions.
Now Steve
clicks on the Escalated Sessions
pulse metric card,
Explore and Filter option.
Now Steve
can dissect this information
by agent, action and topic.
As we saw
the different agent
is causing a lot of escalations.
Similarly, in the actions,
a refund amount
is causing over 454 escalations.
Our topic Credit Card
Refund was involved
in 296 escalations.
So Steve goes to the dashboard
and filters for these agents.
The topic and action
as well.
Now you can see the whole
dashboard got filtered
and faceted for the selections made,
for the agent, topic and action.
Now Steve can also
look at the session table
to understand each of the session.
What exactly happened
by going to the Agent
Builder session page,
and from this dashboard
with a click of a button,
Steve can navigate to the agent
from a new browser tab.
So with this we're
cutting down
at least 20 steps
in terms of navigation.
Now Steve, with a few clicks
and questions,
was able to understand
where the issue was.
Now he can take a decisive action
of how to improve
the topic and action.
And all of this
is powered by Tableau
Next dashboard.
Thank you. Over to you, Carolyn.
Okay.
This is how real time data
turns reactive support
into proactive success.
That is amazing functionality.
And next up,
CRM Analytics
just dropped a batch of smart,
user friendly updates to boost
clarity, control and interactivity
right in your dashboards.
From custom tooltips
and filter
precision to smarter widgets
and repeatable headers.
These enhancements
make your insights
more intuitive than ever.
Mark Tossell, Senior
Product Manager, has it all for you,
so let's check out this demo now.
Well, I'm excited
to demo to you today
the new functionality for repeater
widgets, whereby
you can add a non-repeating element
or a repeater widget header.
So we're going to go into
Edit Repeater content.
And we've got an option here
to add a header. Let's select that.
And then we're just going to drag
repeater
headers
or non-repeating elements
onto the page.
And we can just click on them
to resize them.
And and to move them etc..
And then what we're going to do
is we're going to add
the head of text.
And let's go ahead
and we can,
make that a bit bigger maybe,
and we can bold it.
And then let's go ahead
and let's add
the second one as count,
which is great.
And what we're also going to do
is add some sorting capability
whereby you'll be able to sort
your
elements or essentially columns,
if you're setting up
your repeater widget,
you have like a table.
It isn't technically a table,
but like a table.
So we can go in here
and we should be good to go.
And now you can see
we've got a header up the top.
And we're able
to sort by selecting the header.
A simple but effective enhancement
that's been delivered in
summer of '25
for CRM Analytics
is the ability to add a custom
tooltip header
to the columns in your tables.
The standard functionality,
or default,
is that you'll actually
have the ability here
for the tooltip
to basically just show you
what is in the,
what the column header label is,
which frankly, is not very helpful.
So we're going
to give you the ability
to be able to customize that.
So for example let's go in here.
Go to our column tab
and under let's say
let's pick sales amount.
And we're going to header.
At the moment
this is giving us none.
We could go to default
which would just be
the label itself.
But I want to give the end users
a little boom,
a little bit more context.
So you can use this kind of like,
a contextual data glossary
or data dictionary, as it were.
So this sales amount,
you could put sales for the last
90 days
in AMER to give the end user
just some more context around
what they are actually looking at.
So we've got that day
and now
it's go ahead
and go into preview mode.
And now we can see a helpful
tooltip,
Sales for the last 90 days in AMER.
Very easy to use
for simple enhancement,
but one I think that
will be quite powerful for end users.
So we have some new capability
in CRM Analytics,
whereby we are able to control
whether or not
your widgets
in your target dashboard
receive the global filters
that were applied
in the source dashboard.
So we have an example here.
Let me show you how this works.
We're going to select
a global filter value
in this dashboard.
Then I'm going to select
or click on a list widget
which will take me to
this other dashboard.
And you can see that the
global filter value
was applied to this widget,
but it was not applied
to this widget.
We can see here
the global filter was applied
to the dashboard.
But this widget over here
did actually not receive it.
And that's apparent when you compare
the details for each one.
And we can
see that
we have applied the filter here.
The currency ISO code is EUR.
How do we achieve that.
It's very simple.
By default
widgets will receive those filters
so apply
external filters will be selected,
but we can deselect it
as we have in this widget,
thereby turning off the ability
for that widget
to receive those incoming filters.
Very simple
and hopefully very helpful.
Now I'm going to demo to you
the new capability
for your list and toggle widgets
whereby you are able to
add interactivity.
I've already got this
one here set up.
So we've got a toggle widget,
and we have some interactivity
whereby when you select a value,
so when you select
one of the toggle values,
it's going to link
to this dashboard.
And it's going to carry across
that filter value.
So when I select here
you can
see that it's
navigated to this dashboard.
And it has filtered by the value
that was selected on the toggle.
And just to give you an idea
of how easy this is to set up,
let's go ahead and
we'll go and add a list widget.
And let's select for example
opportunity name.
And we can go create interaction,
select is correct
and we want to navigate
to our test dashboard.
And that's what
we were able to achieve.
All right.
How awesome is that?
It's simple tweaks
that make major impact.
Your dashboards
just got a serious usability glow up
and rounding out our analytics
episode today with Tableau Pulse.
Tableau Pulse is making sure
nothing slips through the cracks
with certified metrics,
smart alerts,
and AI powered Q&A,
reps can spot trends,
ask questions
in plain language, and take action
all before their
first meeting of the day.
Christina Obry,
Senior Director of Product
Management, is here to show it off.
So check it out.
Thanks Carolyn
for this demo of the recently added
Tableau Pulse features.
I'm a pharmaceutical sales
representative
and I start my day
by checking my email today.
I notice that my Pulse Digest
subject line specifically calls out
that a trend change was detected.
This triggered me to open the email
rather quickly,
and indeed,
I can see that
an unfavorable trend was
detected for my market share,
my overall prescription,
and my refill prescriptions.
I need to find out more.
Let's open the market share.
Now on this
Inside Exploration view,
I can get a complete overview.
But before I dive deeper,
let me highlight two important
aspects of this metric.
First of all,
I can trust this metric
because it's been certified.
I can even see who certified it
and when.
And secondly,
this metric actually respects
our company's
custom fiscal calendar.
And I can see that
by the fact
that the current month
starts on April 18th.
Now that I know that
I can trust the metric
and it shows
the correct business dates,
I can inspect the overview chart.
And here I can clearly see
the downwards
trend over the last couple of days.
I can also see that I have been
falling below
the threshold
that we set ourselves
for the market share.
Now, I do recall that
there were additional
alerts as well.
Let me navigate to the
homepage and find out more.
I can
see on the
homepage that I have an option
to explore more polls.
Enhanced Q&A actually suggests
two starting questions for me,
and as I select one, Pulse is
using generative
AI to synthesize
the prescription metrics for me,
I can see that
the new prescriptions are up,
but refills are significantly down.
Let me ask my own question,
as I'm actually meeting
with my leaders
from the Mid-Atlantic regions
this morning.
Let me ask specifically around that.
As I ask my question
in natural language,
the GAI powered
enhanced Q&A,
understood with what I meant
with Mid-Atlantic
regions and Pulse
automatically filtered
on the states
in that particular region.
Looks like I'm not doing too well,
but thanks to Pulse alert
and the ease of exploration,
I know where to dive in deeper
and I can take actions
in my morning meetings.
And that was my update
for Tableau Pulse.
Back to you, Carolyn.
Okay, now that is an exciting update
because it's insight to impact.
Pulse turns your inbox
into a command center.
I absolutely love that.
Well, there you have it.
A jam
packed lineup of releases
for analytics and Summer '25.
Thank you to the team
for sharing
all of the innovation
across Tableau and CRMA.
Make sure you fill out the Q&A
form to get
your questions
answered by the product team,
and tune back into Salesforce
Plus on Tuesday,
June 24th at 12 p.m.
Pacific to hear from this amazing
team directly.
Well, we thank you for joining us
and we will see you in winter.
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Release Readiness Highlights: Analytics
Our Analytics product team has the highlights! Get your questions answered, just fill out this form http://sfdc.co/RRLS-25 and tune back in on Tuesday, June 24th at 12PM PST to hear their answers directly!
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