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>> Hey everyone and welcome back to theCUBE.
Lisa Martin here, with Dave Vellante.
We're covering Snowflake Summit '22.
This is day two of our wall-to wall-cube coverage
of three days.
We've been talking with a lot of customers, partners.
We've got some more partners to talk with us, next.
Informatica.
Two of our guests are back
with us on the program.
Rik Tamm-Daniels joins us.
The GVP, Global Ecosystems
and Technology at Informatica.
And Peter Ku, Vice President
and Chief Strategist Banking and Financial Services.
Welcome guys! >> Thank you!
>> Yes! Thanks for having us!
>> Lisa: Peter, talk to us about what some of the trends are
that you're seeing in the financial services space
with respect to cloud, and data, and AI.
>> Absolutely. You know, I'd say 10 years ago
the conversation around cloud was: what is that?
Right? How do we- >> Dave: Or no way!
(Rick laughing) >> Or no way!
'Cause there was a lot of concerns about privacy
and security and so forth.
Now as you see organizations
modernizing their business capabilities.
They're investing in cloud solutions
for analytics applications, as well as data.
Data, being not only just a byproduct
of transactions and interactions in financial services,
it truly fuels business success.
But we have a term here at Informatica where
data really has no value unless it's fit for business use.
Data has to be accessible in the systems
and applications you use to run your business.
It has to be clean.
It has to be valid.
It has to be transparent.
People need to understand where it comes from,
where it's going, how it's used, and who's using it.
It also has to be understood by the business.
You can have all the data in the world
and your business applications.
But if people don't know what they need it
to use it for.
How they should use it.
It has no value as well.
And then lastly, it has to be protected
when it matters most.
What we're seeing across financial services is that
with the evolution of cloud now really being the center
of focus for many of the net new investments,
data is scattered everywhere:
not just in one cloud environment,
but in multiple cloud environments.
But they're still dealing with many of the
on premise systems that have been running this industry
for many, many years.
So organizations need to have the ability to
understand what they need
to do with their data, more importantly.
Tie that to a measurable business outcome.
So we're seeing the data conversation really
at the board level, right?
It's an asset of the business.
It's no longer just owned by IT.
Data governance brings both business, technology
and data leaders together to really understand:
how do we use, manage, govern and really leverage data
for positive business outcomes?
So we see that as an imperative that cuts across all sectors
of financial services.
Both for large firms, as well as for the mid-market.
>> So quick follow up, if I may. You say it's board level.
I totally agree.
Is it also a line of business level?
Are you seeing increasingly that line
of businesses are leaning in,
owning the data,
building data products, and the like?
>> Absolutely, because at the end
of the day business needs information
in order to be successful.
And data ownership now really belongs in the front office.
Business executives understand that data, again,
is not just a bunch of zeros and ones.
These are critical elements for them
to make decisions and to run their business.
Whether it's to improve customer experience,
whether it's to grow wallet share,
whether it's to comply with regulations,
manage risks in today's environment,
and of course being agile.
Business knows that data's important.
They have ownership of it.
And technology and data organizations help facilitate
that solutions and, of course, the investments to ensure
that business can make the decisions.
And take the appropriate actions.
>> A lot of asks and requirements on data.
That's a big challenge for organizations.
You mentioned.
Well, one of the things that we've mentioned many times
on this program recently, is every company has to
be a data company.
There is no more- it's not an option anymore
if you want to be successful.
How does Informatica help customers navigate all
of the requirements on data,
for them to be able to extract that business value
and create new products and services in a timely fashion?
>> So Informatica announced, what we call the
Intelligent Data Management Cloud platform.
The platform has capabilities to help organizations,
access the data that they need,
share it across the applications that run their business,
be able to identify, and deal with data
quality issue's requirements.
Being able to provide that transparency,
the lineage, that people need across multiple environments.
So we've been investing in this platform that really
allows our customers to take advantage
of these critical data management, data governance,
and data privacy requirements, all in one single solution.
So we're no longer out there just
selling piecemeal products.
The platform is the offering that we provide
across all industries.
>> So how has that affected the way Informatica does business
over the last several years?
Snowflake is relatively new.
You guys have been around a long time.
How has your business evolved and, specifically,
how are you serving the Snowflake joint customers
with Informatica?
>> Yeah I think then, when I'm talkin'
with folks here at the event
there are two big areas that keep coming up.
So data governance, data governance,
data governance, right? >> Dave: Uh-huh.
>> It's such a hot topic out there.
And as Peter was mentioning,
data governance is a critical enabler of access to data.
In fact, there is an IDC study for last year that said
that 84% of executives,- no surprise-
they want to have data driven outcomes
data driven organizations.
But only 30% of practitioners actually use data
to make decisions.
There's a huge gap there.
And really that's where governance comes in
in creating trust around data, and not only creating trust
but delivering data to end users.
So that's one big trend.
The other one is departmental user adoption.
We're seeing a huge push
towards agility and rapid startup of new projects,
new data driven transformations that are happening
at the departmental level,
individual contributors, that sort of thing.
So Informatica, we did a made announcement yesterday
with Snowflake of a whole host of innovations
that are really targeting those two big trend areas.
>> I want to get into the announcements, but the point
about governance and business users being reluctant.
It's kind of chicken and egg, isn't it?
If I don't have the governance, I'm afraid to use it.
But even if I do have it, the architecture
of my company, my data organization may not facilitate that.
And so I'm going to change the architect,
but then it's a wild west. >> Yep.
>> So it has to be governed.
Isn't that a challenge that companies face?
>> Absolutely.
And governance is a lot more
than just technology, right? >> Of course.
>> It's of people process problem.
And there really is a community, or an ecosystem,
inside every organization for governance.
So it's really important that when you think
about deploying governance and being successful:
that every stakeholder have the ability
to interact with this common framework, right?
They get what they need out of it.
It's tailored for how they want to work.
You've got your IT folks, you got your chief data
officer, data stewards, you have your privacy folks,
and you have your business users.
They're all different personas.
So we've really focused on creating a holistic, single pane
of glass, view with our cloud data governance
and catalog offering that really takes all the way
from the raw technical data and actually delivers data
in a shopping cart-like experience
for actual enterprise users, right?
And so I think that's when data governance goes from-
historically, data governments are seen as an impediment,
it was seen as a tax, I think.
But now it's really an accelerator,
an enabler, and driving consumption of data.
Which in turn, for our friends here at Snowflake,
is exactly what they're looking for.
>> Talk about the news.
So data loader, what does that do?
(laughter) >> Yeah!
Well, it's all in the name!
As you say.
No, the data loader it's a free utility
that we announced here
at Snowflake Summit that allows any user to sign up.
It's completely free, no capacity limits.
You just need an email address.
Three simple steps.
Start rapidly loading data into Snowflake, right?
So that first step is get data in there
Start working with Snowflake.
Informatica is investing and making that easy
for every single user out there.
And especially those departmental users who
want to get started quickly.
>> Yeah, so that's a key point of getting data
into the snowflake data cloud, right?
It's like any cloud, you got to get data in.
How does it work with customers?
You guys are known.
You have a long history of extract, transform, ETL.
How does it work in the Snowflake world?
Is it different?
You remember the Hadoop days?
It was...
It was ELT, right?
How are customers doing that today in this environment?
What's different? >> Yeah.
There are a lot of the the same patterns are still in play.
There's a lot more of rapid data loading, right?
As a key theme: just get it into Snowflake
and then work on the data, transform it inside of Snowflake.
So it's a flavor of ELT, right?
But it's really pushing down to the Snowflake data cloud,
as opposed to Hadooop with Spark
or something like that, right?
So that's definitely how customers are using it.
And majority of our customers actually,
with Snowflake, are using our cloud technology.
But we're also helping customers,
who are on-premise customers,
automate the migration
from our on-premises technology
to our cloud native platform as well.
>> Yeah.
And I'd say, in addition to that, if you think
about building a Snowflake environment,
Informatica helps with our data loader solution,
but that's not enough.
Then, now you need to get value out of your data.
So you can put raw data into the Snowflake environment,
but then you realize the data's not actually fit
for business use.
What do we need to do actually transform it,
to clean it, to govern it?
And our customers that use Informatica
with Snowflake are managing the entire data management
and data governance process,
so that they can allow the business to get value
out of the Snowflake investment.
>> How quickly can you enable a business to get value
from that data to be able to make business
decisions that can transform-
deliver competitive advantage?
>> I think it really depends
on an organization on a case-by-case basis.
At the end of the day, you need to understand why
are you doing this in the first place, right?
What's the business outcome
that you're trying to achieve?
Next, identify what data elements do you actually need
to capture, govern, and manage, in order
to support the decisions and the actions
that the business needs to take.
If you don't have those things defined
that's where data governance comes into play.
Then all you're doing is setting
up a technical environment with a bunch
of zeros and ones that no one knows what to do with.
So we talk about data governance more holistically to say
you need to align it to your business outcomes.
But ensure that you have people, processes, roles,
and responsibilities, and the underlying technology.
To not just load data into Snowflake,
but to leverage it again for the business needs
across the organization.
>> So... >> Well. Oh good, please.
>> I just wanted to add to that real quickly, yeah.
One of the things Informatica, we're philosophically focused
on is, how do you accelerate the entire business
of data management?
So with our cloud platform,
we have what's called our ClAIRE AI engine, right?
So we use AI techniques-
machine learning, recommendations-
to accelerate with the knowledge
of the metadata of what's gone on the organization.
For example, when we discover data assets- figure
out is this customer data,
is it product data-
that dramatically shortens the time
to find data assets, deliver them.
And so across our whole portfolio
we're taking things that were traditionally months to do.
We're taking them down
to weeks, and days,
and even hours, right? >> Yeah.
>> So that's the whole goal is just accelerate
that entire journey and life cycle
through cloud native approaches and AI.
>> Yeah. You kind of just answered my question, I think Rick.
So you have this joint value statement.
"Together we help customers."
This is Informatica and Snowflake.
"Together we help customers modernize their data
architecture, enable the most critical workloads,
provide AI driven data governance,
and accelerate added value with advanced analytics."
You definitely touched
on some of those. >> Yeah.
But kind of unpack the rest of that.
What do you mean by modernize?
What is their data architecture?
What is that? Let's start there.
What does that look like?
Modernizing data architecture. >> Yeah.
So, a lot of with so many customers, right?
They built data warehouses, core data,
and analytics systems on premises, right?
They're using ETL technology using
those either warehouse appliances or databases.
And what they're looking for is they want to move
to a cloud native model, right?
And all the benefits of cloud in terms of TCO, elasticity,
instant scale up, agility, all those benefits.
So we're looking to do with our modernization programs
for our current customer base that are on premises.
We automate the process to get them to a fully cloud native.
Which means they can now do hybrid,
they can do multicloud, elastic processing.
And it's all also in a consumption based model
that we introduce about about a year and a half ago.
So they're looking for all those elements
of a cloud native platform.
But they're solving the same problems, right?
We still have to connect data.
We still have to transform data, prepare it, cleanse it.
All those things exist, but in a cloud native footprint.
And that's where we're helping them get to.
>> And the modern architecture these days, quite honestly
is no longer about getting best on-prem tools,
and stitching them together,
and hoping that it will actually work.
And Informatic is value proposition
that our platform has all those capabilities as services.
So our customers don't have to deal with the cost
and the risk of trying to make everything work
behind the scenes.
And what we've done with IDMC-
or intelligent data management cloud
for financial services, retail, CPG,
and healthcare and life sciences-
in addition to our core capabilities
and our CLAIRE AI machine learning engine,
we also have industry accelerators.
Pre-built data quality rules
for certain regulations in within banking.
We've got master data management customer models
for healthcare, insurance industry, all pre-built.
So these are accelerators that we've actually built
over the years.
And we're now making available
to our customers who adopt Informatica's
intelligent data management cloud
for their data management and governance needs.
>> And then the other part of this statement
that's interesting is provide AI driven data governance.
We are seeing a move
toward decentralized data architectures
and organizations.
We talked to Snowflake about that.
They go, "Yeah, we're globally distributed cloud."
Okay, great.
So that's decentralized.
But what we see a lot of customers doing to say,
"Okay we're going to give lines of business responsibility
for data.
We're going to argue about who owns what.
And then once we settle that,
here's your own data lake."
Maybe they've tried to cobble together a catalog
or a super catalog.
And then they'll try to figure out,
some algorithms to determine data quality:
best, okay, don't use.
>> Right. >> Right?
So if I understand it, you automate all that.
>> So what we're doing with AI machine learning is
really helping the data professional.
Whether in the business, in technology,
or in between.
Not only to get the job done faster, better
and cheaper, but actually do it intelligently.
What do we mean by that?
For example, our AI engine machine learning will look
at data patterns and determine, not only what's wrong
with your data, but how should you fix it.
And recommend data quality rules to actually apply them
and get those errors addressed.
We also infer data relationships
across a multicloud environment where
those definitions were never there in the beginning.
So we have the ability to scan the metadata
and determine, "Hey, this data set is actually related
to that data set across multiple clouds."
It makes the organization more productive.
But, more importantly,
it increases the confidence level
that these organizations have the right infrastructure
in place, in order to manage and govern their data
for what they're trying to do from a business perspective.
>> And I'd like to add at that as well.
I think you're talking a lot
about data mesh architectures, right?
That are really kind of popular right now.
And I think those kind of
they live or die on data governance, right?
If you don't have data governance,
the shared taxonomy, these things, it's very hard to,
I think, scale those individual working groups.
But if you have a platform where they
the data owners can publish out visibility
to what their data means, how to use it,
how to interpret it, and get that insight,
that context directly
to the data consumers.
That's game changing, right?
And that's exactly what we're doing
with our cloud data governance and catalog.
>> Well, the data mesh,
you talk about data mesh, there's four principles, right?
It's like decentralized architecture, data products.
Once you figure out those two...
>> Yep. >> You just created
two more problems.
Which is the other two parts of the principle four.
Two parts of the four principles:
self service infrastructure and computational governance.
>> M-hm.
And that's the hardest part
of federated computational governance.
That's the hardest part.
That's the problem that you're solving.
>> Yeah. >> Yeah, absolutely.
Think about the whole decentralization
and self-service.
Well, I may be able to access my data in mesh architecture.
But if I don't know what it means,
how to use it for what purpose,
when not to use it. >> Lisa: No value.
>> You're creating more problems.
>> Lisa: Yeah. >> Than what you originally
expected to solve.
So what we're doing is addressing the data management
and the governance requirements, regardless
of what the architecture is.
Whether it's a mesh architecture, a fabric architecture,
or a traditional data lake, or a data store.
>> Yeah, but I say, I think data mesh is more
of an organizational construct than it is...
I'm not quite sure what data fabric is.
I think Gartner confused the issue.
That data fabric was in the old NetApp term.
You probably work
in NetApp at the time. >> Lisa: Yeah!
>> And it made sense in the NetApp context.
And then, I think Gartner didn't like the fact
that Zhamack Dehghani co-opted this cool term.
So they created data fabric, but whatever.
But my point being,
I think when I talk to customers they're trying
to get more value out of data.
And they recognize that going
through all these hyper-specialized roles is time-consuming
and it's not working for them.
And they're frustrated.
To your points on your joint statement,
they want to accelerate that.
And they're realizing the only way to do that is
to distribute responsibility,
get more people involved. >> Right.
>> Dave: The process.
>> And it kind of dovetails
with some of the announcements we made
on data governance for Snowflake, right?
Is you're taking these operational controls,
the Snowflake layer, that are typically managed by SQL.
And that decentralized architecture data owner
doesn't know how to set
those patterns. >> Dave: Right.
>> And things like that. >> Dave: Right.
>> So we're saying, "Alright, we're creating
this deep integration so that, again,
we have a fit for persona type experience.
Where they can publish data assets, they can set the rules,
and policies, and we're going to push that down to Snowflake.
So when it actually comes to provisioning data
and doing data sharing through Snowflake,
it's all a seamless experience for the end user
and the data owner.
>> Dave: Yeah, that's great. >> Yeah.
>> Dave: Beautiful. >> Seamless experience.
Absolutely necessary these days
for everybody above.
Guys, thanks so much for joining David and me today.
Talking about Informatica: what's new, what you're doing
with Snowflake, and what you're enabling customers to do
in terms of really extracting value from that data.
We appreciate your insights.
>> Thank you!
>> Dave: Thanks, guys. >> Yep. Thank you
for having us.
>> For our guests, Dave Vellante.
I'm Lisa Martin.
You're watching theCUBE's coverage
of Snowflake Summit day two!
TheCUBE'S coverage.
Stick around!
Dave and I will be right back with our next guest.
(gentle xylophone music)