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[UPBEAT MUSIC]
Before every
breakthrough, there's
a question, a
challenge, a moment
that demands clarity.
Because progress
doesn't just happen.
It's discovered
in the patterns,
in the connections,
in the data.
Every question
holds a story,
a story waiting to be
told, a story that always
has a better
narrative when
it's told through data.
And over the years,
those stories
have been brought to life
in an entirely new way
by you, the data fan.
And in doing so,
you've sparked
something powerful.
Because data isn't just
numbers and charts.
It's insight.
It's truth.
It's the engine
of progress.
And now, we're at
the edge of something
new, something
revolutionary,
an era where data
and AI work side
by side to imagine new
possibilities to see
what couldn't be seen, to
do what couldn't be done.
[EXPLODES]
This isn't about
technology alone.
It's about unlocking
potential, your potential,
the potential to
see clearly and move
faster than ever before.
The ability to create
personalized experiences
at scale.
The power to lead
with confidence
in every moment,
the power of
collective intelligence.
To create a world where
every story is heard
and every person
is empowered.
Turning information
into action and action
into impact.
This is your moment,
your opportunity
to make a mark.
The future is not
a distant point
on the horizon.
It's something you shape
right here, right now.
So what will
you do with it?
What story will you tell?
Data doesn't just
reveal the world,
it helps you change it.
Please welcome president
and CEO, Tableau, Ryan
Aytay.
Hello, good morning.
How's it going?
How are you doing?
It's great to see
everyone here.
Wow, look at this crowd.
Over 8,000 of us here.
Pretty amazing.
Welcome to Tableau
Conference.
I am so excited
to be here today.
I see lots of
familiar faces.
What a day, huh?
Here we are, San Diego.
Really great day
here in San Diego.
And I want to just start
off by saying thank you.
It's really
important to me
to say thank you to
all of you, of course,
our customers, our
partners, our community
members.
I see many of you
here in the front row.
Amazing.
[CHEERS]
All right.
Also, very great group of
executives and business
users here.
Our employees, I really
am grateful for all of you
for being here today.
We have a pretty
amazing show for you,
a pretty amazing week.
Our goal is to inspire
you to make sure
that you have a
great opportunity
to learn and
reconnect with people.
And this is, ultimately,
the data analytics and AI
events of the year.
It's pretty exciting.
I know I'm excited
to be here.
I'm honored to be here.
It's pretty fun.
And if you think
about, What do
we have in store for you?
we have a lot, actually.
And a lot of this is built
based on your feedback.
So we do have
Devs on Stage.
Is anybody excited
about Devs on Stage?
[CHEERS]
All right.
[APPLAUSE]
So Devs on Stage is
tomorrow 10:00 AM.
That's going to be
really exciting.
I won't give
anything away,
even though I want to.
We have the Iron Viz.
I see some of the flashing
in the background.
The Iron Viz is
really awesome.
If you haven't been
to an Iron Viz,
I highly recommend you
come and check it out.
Additional to that, we
have our Data Night Out
with Bob Moses.
We have a bunch of
really great sessions.
And oh, by the way, if you
don't see all the sessions
because you're in
other sessions,
we're going to try to make
as many of those available
to you on Salesforce+,
which I know is important.
So we'll do our
best with that.
We also want to say
thank you, again,
to our sponsors.
A lot of sponsors,
a lot of partners,
a lot of customers.
And I think that's
really important for us
to make sure we
continue to reiterate.
Now I talk about the
DataFam quite a bit.
It's at the center
of all of the things
that we work on.
I like to say it's at the
heart of everything we do.
And there's a
lot of momentum.
The momentum continues.
The momentum now, we have
over 5 million Tableau
public profiles, over
25% year-on-year growth.
We also have
over 11.5 million
public visualizations.
And that's all thanks
to you all here.
You've all been
doing that.
You've been driving
the momentum.
You've been doing the user
groups with almost 50,000
user groups, 43%
growth year on year.
It's pretty
incredible, right?
And why is there
all this momentum?
Well, it's really, because
of our amazing DataFam.
And again, I want to
laser-focus a little bit
on this because
our DataFam is what
has brought us
to this place,
has helped the
organizations,
the critical path to
this growing community.
And so the DataFam,
we have, for example,
a lot of folks
I want to thank,
but not enough time,
not enough slides.
I might get in trouble.
But I do want to
say thank you.
We have a number of new
Tableau hall of famers.
We have a number,
of course,
of visionaries
in the audience.
And I want to thank
them and maybe
ask them to stand
up if possible.
If you're
comfortable, feel
free to stand up
if you're able to.
Congratulations.
OK.
Amazing.
[APPLAUSE]
Thank you.
Thank you.
And of course, we also
have our ambassadors.
Who here is an ambassador?
If you feel comfortable
and you want to stand up,
please stand up as well.
[CHEERS]
All right!
If you're an
ambassador and you're
at home or a
visionary, stand up.
[APPLAUSE]
Also, we have
our new group--
sorry, our user
group leaders.
These are the people who
have been to a few user
groups.
Stand up.
You can all stay standing.
It's OK.
[APPLAUSE]
It feels good to stand
up a little bit, right?
OK.
So you can sit down now.
Thank you.
I think it's all
really important, too,
to recognize people
who are new, right?
So people who are here
for the first time,
the first time
Tableau Conference
folks that are
here today, so
let's give them round
of applause as well.
[APPLAUSE]
OK.
And you may be
wondering, Well,
why am I spending
so much time?
Again, it is critical that
we talk about our growing
community, because it
is the heart and soul
of everything we do.
We get our
feedback, we learn.
And when I think
about that,
I also think
about, How can we
take some of the
things that Salesforce
brings Tableau and Tableau
brings to Salesforce?
And so we've been working
on some new things,
and we tried a new
thing this year.
It started yesterday.
We brought
together, of course,
the power of Agentforce,
our digital labor
platform, as well as we
brought together Tableau.
And we said,
hey, let's pull
a couple hundred
people together
and see what happens.
And I thought, I
wasn't exactly sure.
We wanted to
bring it together,
and you're the builders.
We wanted you to
tell us and show us
what's possible.
And this is a
little bit scary,
but we'll call it out.
Yesterday, there
was an earthquake.
OK?
That's not something that
I'm very excited about,
but it is something we
need to be aware of.
And during that,
what I also
found was that this
great hackathon, there
were a few folks that
pulled together Tableau,
an Agentforce, and a
natural language query,
and they were able
to, essentially,
pull together
sort of a-- we'll
call it an earthquake
crisis response scenario.
It's very powerful.
This is the type of thing
that we need in our world
to help us, right?
When you bring together
agentic technology
and of course, the
power of Tableau.
And so I believe we have
Roberto, Rob, and also
Suraj in the audience.
Maybe you're nearby.
Would you-- let's give
them round of applause
for doing such
a great job.
You can stand up.
[APPLAUSE]
Thank you.
Great job.
And by the way, you're
both new to Tableau,
right?
OK, awesome.
And you're 10 years.
Yeah.
Fantastic.
Awesome.
Thank you so much.
Thank you.
Thank you.
So we talk about
here at Salesforce
our values quite a bit.
And our values with
Salesforce and Tableau,
we've been very
consistent to these values
over the last 26 years.
And it's really
critical to us
that we-- no matter
what type of environment
we're in, some things, the
economy, things change,
these are consistent
to us always.
Trust, customer
success, innovation--
we're going to talk a
lot about that here--
equality, and
sustainability.
These are very important.
And what have these
allowed us to do?
These have allowed us
to do well with over $40
billion in revenue
guidance for FY26,
but also do good
at the same time.
I know there are a lot of
people in this room that
do good, and I'm very
appreciative of that.
That is really
our mission.
When you think about
Salesforce and Tableau,
we truly believe
that business
can be a platform for
change, for impact.
And that is what we've
been doing for roughly 25,
26 years with
our 1-1-1 model,
where we put in 1% of
our equity, our time,
and of course,
our product.
And that has been a
really great thing.
And also part
of the reason
that I'm here
at this company.
So that's a little
bit of where we are.
But what we're all
really here for
is to talk about data
analytics and AI.
So what I wanted to do is
go back, go back in time--
not too far,
but far enough--
to 2003, the very
beginning of Tableau.
And that reminded me
of the first version
of Tableau, which
was Tableau 1.0--
early versions.
OK.
Who here used Tableau 1.0
or 2.0 or early versions?
Do we have any hands
in the audience?
Maybe they're shy.
This is pretty regardless.
Maybe you started in
2003 or 2009 or 2020.
Or maybe you
started yesterday,
like some of our friends
were at the hackathon.
The point is, you
started and you
created a movement.
And when I ask people what
happens when you connect
data and you connect
visualization
with Tableau, and I get
this pretty consistent
answer of a lot of joy.
There's an excitement.
And the power of being
able to help people see
and understand data is
very, very interesting
because there's a lot of
people that get excited
about it.
And you've all made that
very special for Tableau
and very special
for your customers
and your organizations
and your nonprofits.
And wherever it is that
you spend a lot of time,
you've told a
story with data,
also evident on
Tableau Public.
And that's great.
But we are
clearly in a world
of significant change--
the AI era, the agent era.
Pick your term.
We're in a
world of change.
It's no surprise.
Everyone's seen
self-driving cars,
I'm sure.
Everyone's seen robotics,
robots on the way, ChatGPT
and different
tools and LLMs
and various educational
institutions.
I saw something
just this morning.
We see the next
version of an LLM
now saying it can do SQL
queries at 93% accuracy.
That's pretty interesting.
So it's exciting, but it's
also potentially scary.
Depends on what
your perspective is.
And so what I hear
from a lot of people
is that there are certain
feelings of uncertainty.
Can I trust AI?
Is it safe?
How can I
prepare for this?
Will it affect my work?
What's the future
of Tableau?
I get that question, too.
Are they going to abandon
Tableau in the new AI
era, agentic era?
Literally, I hear
this question.
Well, there's also
another question.
And I think this is
core to everything
we've spoken about so far,
which is, What does this
mean for you--
for you and for
everyone here?
which is ultimately,
What does
all of this technology,
all of this AI
and agentic capability
mean for you?
Well, it's a
good question,
and it's a question
I get a lot.
And when I think
about that,
it is, OK, let's examine
the world of the analysts
and the data professional
or the site administrator
or whatever else you
would call yourself.
And I think there's
many jobs that you do.
You have a lot
of complex jobs.
Your job is hard,
yes, but it's also,
I think, rewarding
from what I hear.
You're creating
dashboards.
You're doing pet projects
for your executive, which
maybe I asked for
from my amazing team.
You're doing
dashboard layouts,
table calcs, LODs.
Some of these things you
love, some of these things
you don't love.
And I'm not going to
say which ones because I
hear different answers.
But the point is you
have a complicated role.
And that role is critical
to organizations.
And it doesn't matter
where you are located.
It doesn't matter.
It does not matter.
And so in the new
world, in the new AI
and agentic era,
all of that's
going to accelerate.
Data connections are
going to be faster.
You can get data
cleaned much quickly,
much quicker.
It will happen
in a way that you
haven't been able to do.
Everything gets
accelerated.
So again, the question
of uncertainty--
what's going to happen?
Can I trust this?
Is this going to work?
What does it mean for me?
Well, what I will
tell you is your job
is transforming.
Your job is
transforming, and now
is a really great time
to get excited about it.
Because your job
is not going away.
Your job is transforming.
And we are in a world
now where, of course,
your role as an analyst,
a data pro, a site
administrator, is
going to change.
You're a superhero
in the new world.
You're a decision
architect in addition
to an analyst.
Maybe you're a
trust enabler,
an outcomes whisperer.
Pick your term.
You can ask ChatGPT what
other terms they'd like.
The point is, you are in
a transformational moment.
And that moment is
starting right now,
of course.
But it's not just you.
Your company or
your organization
or your nonprofit or your
educational institution,
they're also needing
to transform, too.
They need to
transform from being
data rich and insights
poor because they're
sitting on all
this information.
You know that.
But they need to move
to the future, which
is, I want to be data
driven if I run Tableau.
I want to be data driven.
Ask any other executive.
I want to be data driven.
How do I do that
in an agentic era?
It's a big question.
So let's reflect
for a second.
What is our
job at Tableau?
Well, in 2003-ish and
also at Salesforce,
we helped to define
the traditional BI
environment, the
self-service analytics
environment.
And so our job was to
help define that and help
empower you.
Well, our job now is
to help empower you
for the next era we call
the agentic analytics era.
And that's very important.
But again, I'm
sensing, perhaps,
this feeling of
uncertainty coming back.
What about Tableau,
the current Tableau,
the Tableau I love?
Well, I love it, too--
the Tableau we all
know and the Tableau we
all love.
And maybe you're
a Desktop user.
I'm sure we've got
lots of Server users
here, lots of Cloud
users here as well.
Maybe you're
using data prep.
Maybe you're using
something else
that I don't have
on the slide.
The point is, the
current Tableau is not
going anywhere.
Let me say it again.
Current Tableau is
not going anywhere.
I hear this
question a lot.
But we also need
to transform.
I just said we're all
transforming as people
in the agentic era.
Organizations
are transforming.
Well, we also need to
transform our portfolio
of products.
We need to get to
that next level.
We need to get to
that next chapter.
And so that, really,
is where we are.
And of course, we need
to have a new product
to add to our portfolio.
The name of that
product is Tableau Next.
And I couldn't be honestly
more excited to bring you
the future of what agentic
analytics looks like
because Tableau Next is
the addition to get us
to that next chapter.
And this is where I
want you all to come
on the journey with us.
Now, you may be wondering,
what is agentic analytics?
I'm not clear.
That's our job.
Our job is to empower you.
Our job is to inform you.
Our job is to inspire you
and take you on a journey.
So Tableau Next, at
a very high level,
is all about data.
There's a few data
shirts here, I noticed.
Well, let me talk to you
about the open data layer,
the most open data layer.
It doesn't matter.
Are you an analyst or
a decision architect?
Or maybe it's an AI agent
we're looking to enable
or an organization.
Well, the fuel
and the foundation
of agentic
analytics is data.
Also, you want it
to be harmonized.
You want it to be
orchestrated in a way
that you can take
advantage of it
wherever it is,
any data source.
Now, that's great.
But also, I need to
make sure that there's
semantics on top of that.
So we've built an
AI semantic layer
on top of that as well.
What does that mean
at a very high level?
How do I get the
most trusted insights
from my data
and be able to,
no matter which
organization I'm in,
no matter which
department I
am part of, can
understand and provide
accurate insights to
my analyst population,
my decision
architects, my agents?
Maybe that's
in Agentforce,
my organization at
large, my CEO, my CXO.
It does not matter.
And of course, what else?
What's core to Tableau
is our visualization
capability.
We love this part of it.
We also have a lot
of feedback from you
we need to do certain
things-- modernize
it, make it this,
make it that.
And that's what
we've done.
We've started to do that.
We're bringing
it out to you.
It's now reusable.
You can share it
in a marketplace
internally and externally.
We're going to
show you that.
It's also about bringing
the future of modern look
and feel right.
We all know Tableau has
been around for 22 years.
We're bringing
it to the future.
And then one of
my favorite parts
is ultimately our
integrated action layer.
Integrated action layer--
it's hard to say fast.
But what it
really means is
I want to get insights
wherever I am.
If I'm on the plane, I
want them on my phone.
If I'm in my computer,
I want them in Tableau.
Maybe I want
them in Slack.
Wherever I am,
wherever I work.
Maybe it's in Agentforce.
Maybe it's in some
other tool like Workday.
It doesn't matter, or Box.
I want to get my
insights where I work.
And that is what this
integrated action
layer is.
And so this is what I'll
call a summary of Tableau
Next.
And we're going to show
you, of course, a lot
about this today.
But I'm going
to go back for
a second because this
question of, well, what
about Tableau today?
Well, let me tell
you one more time,
we're not
abandoning Tableau.
We are putting
this together
in one unified portfolio--
Desktop, Server,
Cloud, Prep, and Next.
It's an additional
part of our portfolio.
It is interoperable.
Now, by the
way, that's not
easy to make things work.
But we are committed
to it because you
are committed to us.
And we are on this
journey together.
And so let me
just double down
on my point
around commitment
because I am
committed, and we
are committed at
Salesforce and at Tableau,
to your growth.
We are heavily
committed to this.
And you may not
believe us all the time
because we interact.
And this is part of
being in a partnership.
But we are doing things.
And we're going to
show you some things.
For example, we
will be investing
in Tableau Public.
We will be investing
in our community.
We will be
investing in Server.
We're going to show
you some of this today.
We're also going to be
investing in how we price
and package Tableau,
which is kind
of a new thing for us.
How do we make it easier
for you to get access
to our products?
How do we make
it flexible?
These are the things
that we're focused on.
So I've covered a lot,
and you're probably
ready for the
next chapter.
But I want to just
emphasize one last thing.
We talked about
uncertainty.
We talked about the
opportunity to transform.
We talked about all the
change that's happening.
I am a true, true
believer of the fact
that there are not
jobs going away.
In fact, jobs are
being transformed.
And the time
is now for you,
and the moment is here.
The products are here.
We are here.
You are here.
And this is
our opportunity
to do this together.
So I appreciate your
attention on this.
What I want to do now is
move to the next chapter.
I'm going to keep
saying "next."
It's kind of a new thing.
But we're going to
move into a little bit
of a few demos.
And we're going to start
off with my great friend
and colleague, Southard
Jones, our Chief Product
Officer.
Please welcome him.
[APPLAUSE]
All right.
Thank you, Ryan.
And hello, TC.
Woo.
Woo!
[APPLAUSE]
It is really
great to be here,
right here in San Diego.
I love this town.
Last year at this
time, I stood here
in front of you, and
we shared our vision
for the future of Tableau.
And we asked for
your feedback.
And you gave us lots of
feedback, lots of it.
In fact, over
the past year,
we've had over 100
product review sessions,
from hands-on
products training,
to user experience
reviews, to focus groups--
together, this community,
everybody in this room--
everybody in this room.
And the 1,200 developers
that work at Salesforce
and Tableau have built
the future of Tableau.
Ryan just introduced
it, Tableau Next.
At one point, it
had some other name.
But don't worry.
Tableau Next is here to
stay as a name, I think.
I think.
[LAUGHTER]
Well--
[APPLAUSE]
The fun part-- at least
for me-- the real fun
part now is I
get to show you
the product, the
real product.
Well, I'm actually not
going to show it to you.
I want to take this moment
to introduce John Demby.
Woo.
[CHEERING]
John is going
to be guiding us
through this
demo here today.
So what's the demo?
We created this
fictitious company
called DataFam Kicks.
And we just launched
this new shoe.
It's called the Diego.
Very cool shoe.
We need to launch a
marketing campaign
so we can hit some really
audacious sales targets.
So this demo has
two chapters.
The first chapter
is an analyst.
And you're going to
see the analysts use
Tableau Next to
accelerate their workflow,
help them do data
modeling, creating
calculations,
but at the end
help a business leader
make a better business
decision.
And then chapter
two, we're
going to have a
business leader come up
and have a conversation
with their data.
We'll have a conversation
with that data
so they can deliver a
better business outcome.
All right.
So enough little intro.
Let's get into the demo.
I get to take the
role of an analyst--
my favorite job, Woo
so let's jump in.
I, as an analyst,
I get a Slack.
I get a Slack from
Rekha, my CMO.
And in that Slack, you
see this completely
interactive visual.
This is not a JPEG.
I can click on it.
I can drag and drop.
I can visualize it.
I can do whatever I want.
But Rekha asked
me, hey, Southard,
we just launched
the Diego shoe.
Can you do some analysis,
look at some other
campaigns that we have,
and tell me what we could
do to hit our 35,000--
that's a lot of shoes--
35,000 shoes I want to
sell in the first quarter?
So yes, I'm all over it.
Give me a few minutes.
I can do that in
a few minutes.
All right.
So where do I start?
I start in the Tableau
Next workspace.
What's the workspace?
The workspace
is one place,
As in all of my analytical
assets are here.
I get a complete lineage--
everything from
my dashboards
to my visualizations
to my semantic models
to the actual tables
to the data connections
themselves.
We call it a workspace.
As an analyst, it's
like my dream space.
One place, everything--
I get it all.
And here I go.
So what I need to do
now-- for this, right now
for this project,
I need to connect
to two more data sources.
I need to get data
from Databricks.
I need to get digital
media spend data
from Databricks.
That's structured data.
I also need to get
unstructured data--
social media
reviews from Box.
All right, so
let's jump in.
Let's go to
Databricks, and I'm
going to get that data.
I'm actually going
into Databricks.
I'm not sucking
the data out.
What I'm doing is I'm
looking at Databricks.
I'm actually accessing
the objects down
to the individual tables.
And there's this table
called Conversions.
And now I'm actually
seeing the data
in Databricks.
I didn't move it.
I didn't create extracts.
I'm looking
into Databricks,
and I see the actual data.
Now, what I want to do
now is I want to model it.
So I'm going to create
a semantic model.
All right, so I create
that semantic model.
I take the metadata--
not the data--
the metadata
into my semantic model.
So now you can see
here my semantic model.
I have an existing
semantic model.
This is our semantic
modeling experience.
And I've added
that digital media
content to it.
Again, the data itself
is still in Databricks.
And now I'm going
to model it,
and I want to create
a new calculation.
All right.
Anyone here know
what a CPA is?
No, not a certified
public accountant.
CPA-- it stands for
Cost Per Acquisition.
In the marketing
world, that's
the way we figure out how
much it cost us to acquire
a new customer.
I don't know how to
create that calculation.
I think there's something
called a level of detail
or something.
We'll enter Data Pro.
Data Pro is an agent
where I can just
type in the question,
create a calc for CPA
by channel.
It figures out the
level of detail.
That's nice.
I like that.
It writes the
right syntax.
Awesome.
It does one more
really important thing.
It adds context
to all of that.
And you say, why
is that important?
In two minutes, I'm
going to tell you
why it's really important
that we can automatically
add context to
our calculations.
All right.
So I just did
a calculation
on structured data.
That's pretty cool.
But now I want to analyze
unstructured data.
How do I analyze
unstructured data?
I don't know.
I heard there's something
called a vector database.
I have to learn
how to do parsing.
I might have to do
some other stuff.
Again, I'm not sure
how to do all that.
So I just want to
know one simple thing.
Tell me the number
of positive mentions
for the Diego shoe and
my social media reviews--
simple question.
I will type that into
my Data Pro calc,
and it's going to generate
the formula for me.
Look at that.
Now that's nice.
It also creates all that
business context for me
as well.
Pretty cool.
I like it.
Let's hear it.
[APPLAUSE]
Data Pro is like
my new best friend.
Well, all right.
Now I have a
semantic model.
I've brought AI to
the world of modeling.
That semantic
model gives me
one place where I can
have all of that together,
created this logical
business meaning off
of that raw data.
What's next?
I need to communicate to
my business executives
the question they
asked originally,
which is, which campaigns
can perform the best?
All right, so
let's create a viz.
Do I start from scratch?
Nope.
I have something
called the marketplace.
And in the
marketplace, which
is a gallery of all
of your best practices
I can choose from, it has
all the different things
I can do.
I'm trying to do
campaign performance,
so I'll select the one
that says Performance
Overview.
It gives me a
nice view of that.
And I'm going
to say, great.
What do I get?
I get a blank canvas.
Do I start from a
blank canvas and I can
put some stuff in there?
No, it suggests
metrics for me.
How does it do that?
It knows I'm working on a
marketing semantic model.
It knows I've chosen the
performance overview.
It has information.
It can use that
information,
and Data Pro can suggest
the right metrics for me.
I'll take those
suggestions.
That's very helpful.
One step further,
it says, hey,
how about I fill in the
rest of your dashboard?
I like it.
Yes, fill in the
rest of my dashboard.
That was quick.
Remember, I said
a few minutes.
Literally a few minutes,
we went from raw data
creating a dashboard that
we can have a conversation
about.
But it's not
just a dashboard.
My job is not to
create dashboards.
My job is to help us make
better business decisions.
And there's something
about this viz that's
just not sitting with me.
I need to help
Rekha, our CMO,
figure out cost
per acquisition
versus conversions.
We're trying to hit
35,000 shoe targets.
How do I do that?
Well, I want to
analyze this.
I want to modify this
viz a little bit.
So where I go to
modify this viz?
The beautiful
Tableau authoring
experience that
we know and love,
the award-winning Tableau
authoring experiences.
We made some changes.
We modernized it.
We made it faster.
I can drag and drop.
I can move super quick.
That's great.
But we didn't take
away everything
that makes it great,
the part that all of us
know and love.
So what I want
to do is I want
to figure out and show the
relationship between cost
per acquisition and
conversion rate.
That's an important
relationship in marketing.
I can figure out which
ones cost less than,
maybe, less than
$60 per CPA,
because that's a
critical number for us
as a business.
And I got a perfect
visualization now
that I can share with
my business leader.
And we make a
better decision.
Great.
I got my dashboard.
I'm all good to go.
I'm going to talk to
my business leader,
we're going to be good.
Uh-oh.
I forgot something.
It's not just my
business leader
I need to share this with.
I need to share
this externally
with my digital
media partner.
One click is
the embed code.
I can take that--
literally one
click, my embed
code is right there.
I can take that embed
code, put it in my portal,
and now my external
marketing agency
can see that
information, too.
But here's the
really cool part.
Data security,
permission sets,
authentication all
carried through with it.
I don't have to
worry about it.
They're only going to
see the data they're
allowed to see.
There are a bunch of
campaigns in there.
They're only allowed to
see the campaigns that I
might set them up to see.
That's carried
through automatically.
So I've accelerated
my workflow.
What have you seen?
You've seen an analyst.
That's the fun job.
I just got a lot
faster doing my job
so I can spend more time
having conversations
about how to drive a
better business outcome,
having a conversation
with my business leaders
about that.
That's exciting.
That's what I want.
So this is being an
analyst in the world
of agentic analytics.
Ryan talked about
agentic analytics.
We just gave you a really
quick little glimpse
to that.
But part of
agentic analytics
is driving better
business outcomes.
So let's talk about
driving better business
outcomes with
our CMO, Rekha.
Please join me.
[CHEERING]
Thank you, Southard.
Hello, DataFam.
This is my first TC, but I
have been a long-time user
of Tableau.
I actually start
my day with Tableau
because Tableau
gives me everything
I need to know from
understanding my pipeline,
my revenue, but most
importantly, how
my marketing
campaigns are working.
So that's how
I start my day.
And I had given our
analyst Southard
a quick ask
about giving me
some analysis for our
brand-new campaign.
So, Southard, what
do you have for me?
All right.
I'm really proud of this.
I built this super
cool visualization
and dashboard.
And what you can see
here is the relationship
between our cost
per acquisition
and our conversion rate.
We highlighted a
couple of campaigns
that we want
to mimic so we
can sell a bunch of
these really cool shoes.
Hopefully that gives
you a little bit
of what you need.
Hmm.
I love this analysis.
I love the dashboard.
I love the thoroughness.
But you know what
I really want?
I just want to be able to
understand the combination
of segments and channels
that I can target
with this campaign.
So let's ask Agentforce.
This is super cool.
This is the agent
called Concierge.
You can think of
Concierge as an agent
that allows you to ask
business questions.
Now, what Rekha
just said is the way
that business
people speak.
She didn't ask for
show me this by that
and know the table
names or any of that.
How does this work?
Remember I said, hey,
it's really important
that we have context
and semantics?
It takes the
language she just
spoke, goes to the context
of those semantics,
issues the query down to
the data, and comes back
and generates a response.
Now, that's impressive.
That's what we
call Concierge.
Now, that response is
the context of what
is in this screen as
well as what Rekha said.
But it's not just a
language response.
We're Tableau.
So it's a visual
response because we
want to see and
understand what's
happening in our data.
So Rekha, that's
what you asked for.
And I think it
literally just gave you
the combination of
channels and segments
that you want to target.
OK, so that's a
combination of loyalty
and paid social,
which is great.
OK, this is awesome.
But Southard, real talk.
Can I trust this?
This is the question.
That's what they always
ask, the business owner.
Can I trust this?
Yes.
Yes, you can trust it.
How do I know?
In every single
Concierge response,
there's this thing
called sources.
It's like a citation
in a research paper.
It actually tells
you the reasoning
that the agent did and the
semantic data came from.
It can tell them
exactly where
it is, full lineage,
right there,
available for your
business leaders to have.
How's that?
OK.
So I have a strategy.
I can trust this.
Let's spend $250k to
go reach 100,000 people
to reach our target
this quarter.
So what do I need to do?
What's that strategy
recommendation look
like, Agentforce?
OK, so it's
optimizing around my
paid social and
paid search,
which happens to be two
of my top-performing
channels.
OK, I think we are
ready to move forward.
Last thing.
Agentforce,
can you quickly
summarize this and
send it to me on Slack
so I can go
activate my team?
OK.
And look at that.
So you went from a
simple question about--
I mean, for
those of you who
have worked
with marketing,
this is actually a really
hard problem to solve.
What's the right mix of
channels and segments?
Can you please tell me
how to spend my budget?
And then can you send
it to me in Slack?
Like, we literally
did this on stage
with you live.
Those are complex
questions.
So Agentforce is not
just running a query.
It's actually
doing calculations
behind the scenes.
It's a really
powerful product,
and we just shared
it in Slack.
And so right now, it's
like, hey, you guys are
cliffhanging this demo.
I said, hey, we want
to sell 35,000 shoes.
I just launched
the campaign.
Well, I want to know at
the end, what happened.
Did we actually sell
35,000 shoes or not?
All right, let's
fast forward
maybe six or eight
weeks, and let's see
what happens now.
Are you all ready
to find out?
I'm very excited.
So I get a Slack
from Southard.
Let's pull that up.
Let's see how this
campaign is doing.
Great.
So we reached our target.
We exceeded our
target, 38,000 shoes.
And we still have
$25k remaining.
That's cool.
So that's a
successful combination
of a strategy, the
marketing channels,
and the target.
So let's keep going.
I love that.
Yeah, what you just saw
there was another agent
called Inspector.
I think of Inspector
is a little bit
like an omniscient
caretaker.
Behind the
scenes, Inspector
was running after we
launched this campaign so
that Rekha and I didn't
have to constantly
be watching it.
And it was watching
the performance
of the campaign at
the same time it was
looking at our budget.
And it just alerted
Rekha that, hey,
you're exceeding
your target,
yet you still
have $25,000 left.
What do you want to do?
Do you want to
double down?
I'm ready to go.
Clearly it's working, so
I accept the suggestion.
And I can actually approve
this right from my Slack.
That's the cool part.
So thank you,
Analyst Southard,
for giving us
great analysis
and for running a
successful campaign.
Thank you, Rekha, for
being the part time
CMO at DataFam Kicks
and the full-time CMO
at Tableau.
[CHEERING]
All right.
So what did we
just show you?
What did you just see?
We saw that
analyst workflow
where I got to do the fun
job of being an analyst
in the agentic era.
My job was accelerated.
I spent more time trying
to analyze that data
and get to something that
could help a business
leader make a
smart decision on.
You also saw a
business leader
having a conversation
with their data,
asking complex
questions, somewhat
hard-to-answer questions
in their own language,
in a way that was relevant
to that particular
business.
DataFam Kicks, We
have our own language,
and that drove a better
business outcome.
Hopefully, we
just showed you
a picture of what
analytics looks
like in the agentic era.
So with that, I
want to say, well,
how did that work?
Like, what's
actually happening
behind the covers?
All right, let's
show a quick view
of what it looks
like for Tableau
Next [? marchitecture. ?]
And Ryan just
talked about these before.
I'll just quickly
summarize it.
So that open data layer--
you saw me access
data in Databricks
through zero copy.
I didn't move the
data into Data Cloud.
It stayed in Databricks.
I queried it live.
Semantically,
I modeled that
with data that was
existing inside of Data
Cloud, maybe my
unified individual.
And then I also
combined that
with data that was from
Box, unstructured data.
That's a really
powerful scenario.
I modeled that through
a semantic layer.
We brought AI to
semantic modeling.
I accelerated the path
of building calculations,
level of detail,
unstructured data, one
single source of truth,
yet I didn't also
change that
semantic model.
I extended it.
That means I get
to keep governance
at the same time as
providing agility.
You saw the
visualization layer come
to life, the new,
modern, faster, quicker,
rounded corners,
beautiful-looking
visualization platform
that we can all
use to help our customers
and our end business users
see and understand
that data.
And finally, you
saw the action layer
come into play, where
it was integrated
inside a Slack.
And if you're
unfortunate enough
to have to use Teams, it
will work in Teams also.
[LAUGHTER]
And that final
workflow, which
I can press a button,
and it can kick off
a workflow anywhere.
Now, what we didn't
really show a lot of
was marketplace.
I showed it really
briefly because we just
didn't have enough time.
But marketplace is my
gallery for all my best
practices.
We show it
[? pick ?] a viz.
But marketplace works
for semantic models.
It can work over
data connections.
It can work for workflows.
Any of those things
can be reused.
And you saw those agents,
Data Pro, Concierge,
and Inspector,
come to life,
helping accelerate
our workflow
and drive to
better outcomes.
All right.
So a demo is exciting.
At least, I find
it exciting.
Hopefully, you
found it exciting.
There's nothing
better than a demo
than a real live customer
who uses the product.
So with that, what
I'd like to do
is roll the film and show
how Box is using Tableau.
[VIDEO PLAYBACK]
- We want to run an
AI-first company end
to end.
Everything that we do
operationally at Box
is oriented around how we
can use AI to accelerate
our business.
We think this is a
huge breakthrough
to help enterprises be
able to access, share,
collaborate, and now
bring intelligence
to their most
important data
in their organization.
We now have about 120,000
customers on the platform.
- 68% of the Fortune
500, heavily-regulated,
highly detail-oriented
industries--
financial services,
insurance, government--
- --millions of users,
hundreds of billions
of files, hundreds of
thousands of contracts.
But we've never been able
to tap into the insights
in that data.
The big breakthrough is,
what if I could deploy
AI against all of
this information
and start to understand
my business in completely
new ways?
How do we start
to turbocharge
the productivity of
120,000 companies that are
using Box already,
where actually,
probably a very
significant percentage
of them are also
using Salesforce?
- When you bring
in Salesforce,
the problem that
you're solving
is to get closer
and more connected
with the customer.
- For several years,
I've had this vision
where we could
start bringing
all the operational
data that we need
to gather in one tool.
And to me, it made
sense to do Tableau.
- If you take the
before state--
hey, the CEO is
having a conversation
with the board--
- --when the C-suite
is like, hey,
I need year to
date right now--
- --what was our mean
time to resolution?
- --we need it
in two hours.
- People are
scrambling in the back.
- Like, you can have
it in 30 seconds
with Tableau Pulse
if you already
have the data there.
- And this is where
Tableau solved
a business-critical
problem for us.
- Suddenly, you
had this data
that gives you that
information that you
can pivot at will.
- Tableau gives
us that ability
to take the insights
happening from our product
and service delivery and
marketing and campaigns
and sales, and gives
you that single view
across the business.
If I go one or two
days without seeing
that set of metrics, I
kind of feel high anxiety
and like I'm
missing something.
- We start to think
about now the innovation
that Salesforce
is bringing
to the table in terms of
Agentforce and Tableau
Next.
- Oh, my god.
Oh my gosh, I have been
so excited about this.
With Tableau Next, you
can use natural language,
so you don't need
to be an expert.
You can tell Tableau
what you need to do
and it will to create
that pipeline for you.
- This is a pretty
wild concept
because it's actually
very similar to how
people work.
I might go and ask
somebody in Slack.
If I say, hey, do you
have a document that
has this kind of
information in it?
And they'll go and
spend 5 or 10 minutes,
go and find it.
We're going to see the
same thing happen with AI
agents, except it'll
be 100 times faster,
and you'll be able to
do it for any use case.
And the really
powerful thing
is that you could do
it a thousand times,
a million times,
hundreds million times,
and not drain
the resources
of your actual
human employees.
We just really
think about it
as giving knowledge
workers superpowers
in everything that
they're doing, which
lets us better serve
customers, lets
us innovate faster, lets
us get to market better.
And that's a huge boon for
all of our productivity.
- Putting all of
the business process
parts of my job
into Tableau
will save, bare minimum,
150 to 160 hours
per quarter.
- We've really made
a very well-educated,
calculated bet
on Salesforce.
- I'm looking at a
Tableau interface one
way or another on a daily
basis around something
in the organization.
It gives me a very clear
pulse of what's going on,
how are we serving
our customers.
I don't know how we'd run
the company without it.
[END PLAYBACK]
All right.
Please welcome Ravi Malick
from Global CIO, Box.
How are you?
Come on up.
I'm doing well.
Thank you.
Go ahead.
Well, first of all, I
want to say thank you
for coming.
And it's really great to
see all the progression
you guys have
made with Box,
really amazing things.
And maybe just give us
your first impressions.
How's Tableau Conference
for you, day one?
It's great.
Thank you for
having me here.
It's great to be amongst,
I guess, data royalty.
Is that it?
That works.
Is that a word?
DataFam, Data royalty.
That was fantastic.
It's great to be
back in person.
Great to see
the attendance
and excited about what
you've seen on the screen
and what you guys
have talked about.
Really, I think
we're in a place
now with technology
that is just--
it's amazing.
It's exciting.
You can see the
smile on my face.
I'm like, this
is fun stuff.
I mean, it really
is fun stuff.
Yeah.
Well, I know you
and, I think,
Michelle is
here somewhere.
Hi, Michelle.
Michelle's right there.
Yes.
Thank You, Michelle.
I want to make
sure that we also
give an opportunity.
You guys have done some
really great things
I've seen with Box AI, and
we're partnering really
nicely together.
But one of the
other things
that I'd love to just
maybe hear a little bit
about is if you can
talk about the history
of Tableau or how you're
using it to run-- you've
got a global business.
You're a CIO.
What are you doing
with Tableau today,
and maybe with
Tableau Pulse?
So Tableau, it
actually predates me,
before I came to Box.
But we've really
accelerated it, I think,
over the last
several years.
It is our platform
for intelligence.
We, like many companies,
we're data driven.
We have a very healthy
appetite for data.
As you heard our
CEO talk about,
he's constantly looking
at the different metrics.
And like many companies,
we have different sources,
right?
And to be able to
navigate and stitch
those sources together
is incredibly important.
And Tableau
does that for us
as we're trying
to consolidate
the underlying data
infrastructure.
You can't wait
until you've
completed all that work.
So Tableau gives
us the ability
to get that insights,
to be insights rich,
and still continue to
evolve from a data source
perspective.
And it breaks
down those silos.
And we use it across
the entire business
from engineering and
product management,
to sales marketing to
people, IT, and now
security.
And the recent
phase of our journey
was bringing that into
the global security
organization and
really addressing
a lot of the challenges
that you heard
Michelle talk about a
little bit there in terms
of it was high energy to
produce the metrics that
are critical to
our business.
If you think about
what Box does
and the highly sensitive,
highly confidential data
that is in our platform,
the type of customers
that we have, security
is paramount for us.
It is certainly
number one.
And making sure that
we have that visibility
and we have the insights
into how we're responding
and what threats we need
to keep track of and what
intelligence
that's coming in
and how is that
translating
to our metrics, that
information is top of mind
for the board, certainly
audit committees, top
of mind for our
CEO, and certainly
for me and the CISO.
But the energy
it would take
to answer a question
would be, hey, OK,
we need to go
download the data,
put it into a spreadsheet.
OK, I need to make sure
that that's correct.
And do I have all
the data sources?
And so just the foraging
for data and then--
I use the food analogy--
the preparation of it,
the cooking, and making
sure that it's presented
correctly--
Good metaphor.
--that took a
lot of energy.
I mean, you heard
Michelle, 120, 160 hours.
And that's just
one person.
So think about all
the other folks
that are probably
putting eyes on this.
Moving to Tableau
massively changed the way
that we do that
to the extent
that I think I can--
Oh, you're going
to show us.
--show you here.
Even better, yes.
Do you mind if
we get a camera?
Yeah, sure.
OK, here we go.
I don't know if we
can bring a camera.
This is a live
demo, so I'm
sure everybody's
cringing right now.
Hopefully your company
is not watching.
Yeah.
Look at that.
All right, it came up.
Right.
So I can, if I'm in the
audit committee meeting
or board meeting or
I'm talking to our CEO,
which you heard he's
on Tableau constantly,
I get direct
access to this.
If there's an
incident going on,
I can check our mean time
to respond and actually
see what is going on.
I can check, and I can
go in and figure out, OK,
how are we doing?
Based on what we
see in the forecast,
what we see in
the environment,
is this something that
we need to dial into?
And this is powerful--
direct access to the data
and being able to
get those insights
and make calls right.
And when you're
responding to an incident,
time is incredibly
critical.
So the fact that
we don't have
to wait several
minutes, that we
don't have to worry about
the curation and all this,
that we can get direct
access to the data,
the CEO can get direct
access to the data,
massively improves
our response time.
Yes, our CEO
likes data, too.
Yeah, no.
Yeah.
Well, thank you
for showing that.
Let's give Ravi
round of applause
for showing his
demo, by the way.
Pretty cool.
[CHEERING]
Maybe one last question.
Because we're
showing a lot,
we're talking
about the future,
you saw Tableau Next, kind
of a little conversation
about agentic analytics.
You guys are obviously
pioneering in AI.
And I see all the
things you're doing
and Aaron's doing.
Are there any wish list
items or things you
want us to think about?
Or are there
things, maybe,
that you're
excited to try out?
Like, any feedback for
us or anything else
for the room?
Well, I'll take
the opportunity
to just put a
shameless plug.
I love the Tableau Box
integration metadata.
I think there's tons of
upside and opportunities.
Yeah, I think we've
already connected on this.
But I mean, I love what
you guys are doing.
The Concierge, I
think that's one
of my favorite things
because typically,
those things, I'm
sending a Slack message
or sending an
email to somebody,
and then I'm waiting.
I'm kind of waiting to--
Nobody likes to wait.
Yeah.
And that, now I have
direct access to data,
so I can ask the kind of
questions that typically
would have eaten
up time from one
or multiple members
of the team.
And the nice thing
about that is that now,
we have folks who are
really able to truly 10x,
which is one
of our values,
10x their ability--
10x.
10x sounds good.
Yeah-- 10x their
ability to bring value
to the business.
So instead of,
again, foraging
and the preparation
and the cooking,
they're consuming and
analyzing the meal.
They're telling
you, hey, it
needs a little
bit more salt,
maybe we need some veggies
in here, things like that.
Fine-tuning.
Yeah, fine-tuning
and as you
showed in the
demonstration,
really dialing into what's
going to move the needle.
Amazing.
Well, we're very
grateful for you, Ravi,
and also for Michelle
for being here.
She's not there anymore.
She's the real
star of this.
But thank you so much.
Thank you to Box and
really appreciate
you coming to
Tableau Conference.
Thank you.
Appreciate it.
Appreciate it.
Thank you.
All right.
[CHEERING]
OK, great.
So we are now going to go
and show a little bit more
and talk a little bit more
about DataFam, et cetera.
And I'm going to ask
Rekha, our amazing CMO,
to come on up.
Thank you.
Thank you so much.
Thank you, Ryan.
And thank you, Ravi.
Thank you for being here.
We appreciate
your partnership.
So, four months--
that's all I've
been in this role.
But I've been a power
user of Tableau.
In the last four months.
I have been working, or
talking to, at least,
a lot of you and a
lot of our customers.
So the next set of slides
are going to be with that.
And I need my clicker, if
I can get it real quick.
Thank you.
So the first thing
that I will say
is there is one thing that
comes up again and again
and again in every
single customer
conversation, which is how
mission-critical Tableau
has been to that
organization, the command
center of the
organization.
Tableau's belief
has always
been if we
empower everyone
with the right
tools, people
can do extraordinary
things.
And that's what
DataFam, all of you
have been doing across
incredible organizations.
The next thing that
I want to highlight
is the product, the
mad respect and passion
that all of you have
for this product.
I love this product,
but seeing it
through your lens is
pretty phenomenal.
So I want to bring
back what Ryan said,
which is the
product family
portfolio that we
have for Tableau works
across the board.
It's interoperable,
which means
you can use one
product, or you
can use many products
as you see fit.
Every organization has
different use cases.
You're all tackling
different challenges.
And we are empowering
you with the tools
that you need to go
do your job much,
much better.
And I know you all have
this question in your mind
about how do
I get started?
What is agentic analytics?
What is this?
How can I get started?
How do I create my vision?
How do I create
processes around it?
How do I create the
organizational design
around it?
We hear you.
We have your back.
We always do.
So this is why we are
giving you a blueprint
framework, a step-by-step
tool to go exactly
do that.
Use this.
Download the QR
code so that way,
you can go get started
with your agentic
analytics journey today.
And the one
thing that I am
particularly passionate
about is this community.
I have talked to
so many of you.
It's so clear
why this clicks
and why this is so
unique to Tableau.
You are all there
for each other.
You're sharing
best practices.
You're thinking about
ways to uplift each other.
This, I will tell
you again, is unique.
It's nothing like we've
ever seen anywhere.
And that's the heart
and soul of Tableau.
We also hear that
you want to continue
the conversation in a
place where you all are.
So we are giving you a
brand new Slack workspace
for the community.
You can go
create channels.
You can continue
the conversation
whether you're a data
newbie or a data rockstar
or somewhere in between.
No problem.
You have each
other to help
us get through this
agentic AI era.
So scan the QR
code, and I'll
see you on Slack to
continue the conversation.
And speaking of DataFam, I
have the distinct pleasure
of interviewing someone
who has done a really,
really cool thing.
To do that, please
welcome Harim Jung
to have a conversation.
[APPLAUSE]
So Harim, thank you.
Thank you for
joining us today.
I have heard
your story, but I
would love for all of us
to understand your story,
too.
So tell us a little
bit about yourself
and what you have done.
Of course.
Hello, everyone.
Thank you for having
me here today.
This is Harim.
I'm a Tableau
Public Ambassador.
And I care deeply
about climate change.
That is a topic
that everyone knows.
But when it comes to
explaining what it truly
means, including myself,
many people struggle.
And it's not because
we are unaware.
It's naturally complex.
And that's why I devoted
my work to bridging
the gap using Tableau.
I love that.
And when I tell
these stories,
the chart I
rely on the most
is the radial bar chart.
As you may know,
it's really powerful.
You can bring together
trend, pattern, scale,
even your stories
in one visual.
And that is why I put it
in our cumulative carbon
clock as a key tool of the
Visual Climate library.
I love that.
If you all walk by
the Data Village,
there's a whole
viz gallery.
And this is prime
and center in that.
So you can all take
this for a spin.
But I absolutely
love that story.
How did you get started
with all of this?
How did you get--
fall in love with
data, Tableau?
And what did this
community do to help you?
Right.
That's a really
interesting question.
I started using
Tableau back in 2019,
when I was working as
a nuclear data analyst.
I know the data I dealt
with was incredibly
complex and time
series heavy.
It was really tough
for me only using
the traditional tools.
But after I met
Tableau, I realized
something important.
Data visualization can
be its own language.
It was not only helping
me to tell the numbers,
but helping me to
tell the stories.
And at the same
year, luckily, I
could start my
Tableau Public journey
and being a member of
the DataFam community.
And honestly, that's where
the idea of the Visual
Climate started, even
five or six years ago.
So I'd love to ask you to
join the DataFam community
and be the Tableau
family member.
I promise that
was not a paid ad,
but this is
just her saying
this out of the
sheer excitement
that she has with the
DataFam community.
Thank you, Harim.
The next question
I have for you,
I'm just curious
to get your take
on the modern-day analyst.
You heard Ryan talk
about the role changing,
transforming.
What is your take on that?
Right, Rekha.
That's a really
good question.
Many people
often ask, hey,
AI is just
advancing so fast.
Is BI already over?
What about our job?
And I don't believe
that because AI is not
the end of something.
It's expansion of what
we do as data people.
Let's think.
At the core,
we are the ones
who define the questions,
connect the dots,
bring the meaning,
and turn it
into stories, right?
Instead, AI helps us
move faster, cut out
the repetitive work,
and save the space
to think strategically.
So if we bring Tableau
into this mixture,
AI, especially
Tableau Agent,
becomes our
intelligent partner.
So for me, AI plus
Tableau is evolution
of the storytelling
and revolution
of the visualization.
Love that.
We are getting a marketing
campaign ready with that.
Last question.
What advice would
you like to give
everyone who is getting
started in their AI
journey?
Right.
So for me, AI is
not about the speed.
Its tool for devs.
Like you know,
Tableau Agent
helps us to make
better question
and rich, compelling
visualization, wiser
and faster.
And honestly, that's how
I created Visual Climate.
Visual Climate is
a global initiative
driven by the DataFam.
And we are building
world-first AI-driven
climate dashboard
library, especially
using Tableau Agent.
Of course, it's free,
open to everyone.
And even organizations can
manage their carbon impact
later.
So overall, the AI is not
only about automation.
It's more like
a connection.
Like, we are
all here, right?
It makes our
stories clear,
connection stronger,
and impact wider.
So today, hey,
DataFam, I'd
love to ask you to join
and learn Tableau Agent.
And if you have
any questions,
reach out to me.
Reach out to DataFam.
We are here to support
your Tableau journey.
Oh, Rekha.
One more thing.
Yes?
I can't wait to jump
into Tableau Next.
Oh, yay.
I'm excited for you
to try this, too.
Right.
Well, give a big
applause to Harim.
Thank you so much
for joining us.
[APPLAUSE]
You know, honestly, this
is truly what fuels us.
And this is
why we continue
to build products
that truly
make a difference in all
of your everyday lives.
And we talked a
lot about Next.
And like Ryan
said, we are not
abandoning the rest of
our product portfolio.
We have a lot of
innovation coming.
To do that, please
welcome back this time
Chief Product
Officer Southard.
[APPLAUSE]
Thank you.
All right.
So we've talked a lot
about the agentic era.
We've talked a lot
about Tableau Next.
Some of you are
asking, hey,
what about Tableau
Cloud, Tableau Server?
I saw some
slides about it.
Are you doing
anything there?
So as the person who gets
to make the decisions
on where we're
investing our money
and our resources,
what I can tell
you is that we are
spending more resources
on Cloud and Server than
we even are on Next.
And over the
past year, we've
delivered over 130
different features, all
of them of which
you have asked for,
in Cloud, Server,
Desktop, and Public.
Now, this is just a
short list of them.
And if you're looking
at this list saying,
but where is my feature
that I really want?
I would encourage you to
scan that QR code right
there.
That will take you
to the idea exchange.
That is how we make
prioritization decisions
and product.
Your input drives
our roadmap.
So check out the
idea exchange.
We launched this, and
people have really
been great about it.
Our product team looks
at this every week.
That's how we decide what
we're going to build.
So this is your
opportunity.
Meet your community
members here today.
Make sure you get your
favorite feature voted up,
and that will make sure
it gets into the roadmap.
All right, so that's
great about what
we've done there.
We also made it a promise
to all of you last year.
We said, hey, we're
bringing in Tableau
to Hyperforce.
And you say, what's that?
Hyperforce gives
us the ability
to show Tableau
or have Tableau
be hosted in a number
of different regions.
So we said, hey, we're
going to bring it
to you in two regions.
Last year, we said,
we're going to bring it
to a bunch more.
So right now today, we've
delivered on that promise.
Tableau is now available
in nine different regions
around the world.
So for all of you who
have global organizations,
you can now get
Tableau running
in North America,
Europe, APAC, Southeast
Asia, Australia.
So that gives you a
lot of flexibility
and brings enterprise
credibility to Tableau.
Also, you may have heard
about this announcement
with Google
and Salesforce.
What does that mean?
In short, what
that means is
Tableau is going to
be available on GCP
in the future.
So if your organization
runs on GCP
and you want to use
Tableau in that cloud
environment, you'll
be able to do that
in the future as well.
So, what if you don't
want to be in the cloud?
How many people
here run Server?
[CHEERING]
Sure.
Yeah.
Yeah.
People are shy.
I know there's way more.
All right.
So people have
asked, when are you
bringing AI to Server?
I showed that slide
and you already saw it.
So the answer is now.
If you don't
believe me, I'm
going to do a demo
of it right now.
All right.
So I'm going to
log in to Server.
I've prepopulated
the password.
And for this demo, I'm
going to be a supply chain
executive.
And I have one
simple question.
That is, these tariffs
are freaking me out.
And I need to know,
hey, are some suppliers
going to be at risk
because all these tariffs?
Well, I have a
Tableau dashboard
that helps me have
a beautiful picture
of everything that
I'm doing inside
of my supply chain and
inside of procurement.
And this is what
I use every day
to run my business.
That's fantastic.
But again, I have
one simple question.
And that is, I
want to find out
what my commodity
suppliers are
and if they're at risk.
So what if I had a
dashboard extension that
allowed me to
ask a question
like, which suppliers have
the highest purchasing
volumes below
average price?
Those are
commodity suppliers
that could be at risk.
So I'm asking that
question of an agent.
Now mind you,
I'm on Server.
This is not
something on Cloud.
And that question is going
to come back and give me
a response
that's based off
of my data inside of a
Tableau published data
source.
Live demo.
Fully live demo.
It's available to
all of you today.
So what did you just see?
That question went into--
in this case, it was
a LangChain framework
that talked to an LLM
that turned that question
into a query that we
were able to answer
through the VDS service.
The result of that
query came back.
We summarized that
response, again,
in that LangChain
framework through an LLM,
and gave you an answer.
All of you can
do this today.
If you're really
interested in this,
there's a breakout
session on it.
I encourage you
to go to it.
The power of AI can be at
your hands for everybody.
So with that, I think
we're showing you
how we can bring
AI, whether or not
you're in Cloud,
whether you're
in server, whether you're
using Next, all of them
together.
Now I'll turn it
back to you, Ryan.
All right.
Thank you, sir.
[APPLAUSE]
OK.
I'm going to close
this out here.
I want to say again,
thank you for being here.
There's a couple of
really important things
I want you to come to
if you have the ability
to come--
number one, True
to the Core.
That is your opportunity
to give us real feedback.
Sometimes, it's a
difficult session for us,
but we like it.
We like to hear
your feedback.
Please come.
Iron Viz,
tomorrow at 4:00.
Of course, we have
Devs on Stage.
That's really the
most exciting thing
you're going to see.
So let's give round
of applause for Devs
on Stage.
All right.
You must come.
You must come to
Devs on Stage.
We've got our Data
Night Out, et cetera.
I have one other
thing that we
were going to talk
about, and I'll just
mention it here.
We told you
we're going to be
investing in our DataFam
and Tableau Public.
We are going to be
bringing Tableau
Agent to Tableau Public.
That'll be happening soon.
Just to reiterate,
we're going
to bring Tableau Agent
to Tableau Public.
That will be coming soon.
And additional to that, we
have this thing coming up,
this pretty amazing
event called Dreamforce.
You're going to see a
lot more of Tableau Next
there, as well as well as
some of the Tableau Cloud
and Tableau Server and
other innovations you'll
see at Dreamforce
in October.
And then you may have
noticed this slide pop
up before.
We're going to have
another Tableau
Conference.
[CHEERING]
So I hope you'll
join us next year.
It will be in May, May
5th through the 7th.
And I just want to, again,
thank you for being here
today.
I want to get you off
to your next session.
Please give us feedback.
We do want it.
And we want to hear
all your feedback
throughout the week.
So thank you so much,
and have a great rest
of the event.
[MUSIC PLAYING]
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