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>> Good morning live from Las Vegas at Snowflake Summit 22.
Lisa Martin with Dave Vellante.
Dave, it's great.
We have three wall to wall days of coverage
at Snowflake Summit 22 this year.
>> Yeah, it's all about data
and bringing data to applications.
And we got some big announcements coming this week,
super exciting.
>> Collaboration around data.
We are excited to welcome our first two guests
before the keynote.
We have Sunil Sunan SVP of Data and Analytics
Service Offering Head at Infosys and Chris Degnan alumni
is back with us the Chief Revenue Officer at Snowflake.
Guys, great to have you on the program.
>> Thanks for having us.
>> Thank you for having us.
>> Sunil, tell us what's going on with Infosys and Snowflake
and the partnership.
Give us all that good stuff.
>> Yeah, I think with the convergence of
data, digital and computing economy,
that convergence is creating so much possibilities
for our customers, Snowflake and Infosys working together
to help our customers realize the vision
and these possibilities that are getting driven.
We share a very strategic partnership
where we are thinking ahead for our customers
in terms of what we can do together
in order to build solutions,
in order to bring out the expertise
that is needed for such transformations
and also influencing the thinking
and the point of view in the market together.
So that, there is cohesive approach
to doing these transformation
and getting to those business outcomes.
So, it's a partnership that's very successful
and it's strategic for our customers
and we continue to invest for the market.
>> Got some great customers,
some of my favorite CVS, Nike, Williams Sonoma.
Got to love that one.
Chris, talk to us about the Snowflake Data Cloud.
What makes it so unique and compelling in the market?
>> Well, I think our customers really,
they are going through digital transformation today
and they're moving from on-premise to the cloud.
And historically speaking,
there just hasn't been the right tool set
to help them do that.
And I think Snowflake brings to the table
an opportunity for them to take all of their data
and take it and allow it to go from one cloud to the other.
So it can sit on AWS, it can sit on Azure, it can sit on GCP
and it can move around from cloud to cloud
and they can do analytics on top of that.
>> So data has been traditionally really hard,
and we saw that in the big data movement.
But we learned a lot.
And AI has been challenging.
So what are you seeing with customers?
What are they struggling with
and how are you guys helping them?
>> Yeah.
So if you look at the customer journey
they have invested in a number of technologies in the past
and are now at a juncture
where they need to transform that landscape.
They have the challenges of legacy debt
that they need to get rid of or transform.
They have the challenges of really bringing
a cohesive understanding within the enterprise
as to what these possibilities are for their business
given the strategies that they're pursuing,
business and IT cycles are not necessarily aligned.
You have the challenge of very fragmented data landscape
that they have created over a period of time.
How do you put all these together
and work with a specific outcome in mind
so that you're not doing transformation
for the purpose of transformation
but to be able to actually drive new business models
new data driven products and services,
ability for you to collaborate with your partners
and create unique competitive advantage in the market.
Now, how do you bring those purposes together
with the transformation that's really happening?
And then that's where our customers,
grapple with the challenges of bringing it together.
>> So, Chris, how do you see it?
Because somebody was talking about legacy debt,
I think technical debt,
you kind of started out making the data warehouse easier.
Then this data cloud thing comes out
and you're like, oh, that's an interesting vision.
And all of a sudden, it's way more than vision.
You get this huge ecosystem, you're extending,
we're going to hear the announcements this morning.
We won't spill the beans,
but really expanding the data cloud.
So, it's hard to keep up with where you're at.
So I think modernization.
So how do you think about modernization?
How are your customers thinking about it
and what's the scope of Snowflake?
>> Well, I think historically you asked about AI and ML
and in the AI world historically they've lacked data.
And I think because we're the data cloud
and we're bringing data and then making it available
and democratizing it for everybody.
And then, partners like Infosys are actually helping us
like bring applications and new business models
to the table, to our customers.
And they're innovating on top of the data
that we already have in the Snowflake Data Cloud.
>> Chris, can you talk about some of the verticals
where you guys are successful with Infosys?
The three that I mentioned are all retailers,
but I know that finance, healthcare and life sciences
are huge for Snowflake.
Talk to me, give us a perspective of the verticals
that are coming to you guys saying,
"Help us out we got to transform."
>> Well, I'll give you just an example.
So, in the retail space, for example,
Kraft Heinz is a joint customer of ours.
And, they've been all in on Snowflake's Data Cloud.
And one of our big customers as well is Albertsons.
And Albertsons realizes, oh my gosh,
I have all this information around the consumer
in the grocery stores
and Kraft Heinz, they want access to that
and they actually can make supply chain decisions
a lot faster if they have access to it.
So, with Snowflake's data sharing,
we can actually allow them to share data,
Albertsons share data directly with Kraft Heinz,
and Kraft Heinz can actually make supply chain
decisions in real time.
So, these are some of the stuff that Infosys and Snowflake
help our customers solve.
>> So, traditionally, the data pipeline
goes through some very highly specialized individuals
whether the data engineer, the data scientist,
the data analyst.
So that example that you just gave,
our organization, you mentioned before democratization.
>> Chris: Yeah.
>> So democratization to me as a business person,
I actually can get access to the data.
So, in that example that you gave
between Kraft Heinz and Albertsons,
is it the highly hyper specialized teams sharing that data
or is it actually extending into the line of business folks?
>> Well, so that's the interesting part for us
is I think Snowflake, we just recently reorganized
my sales team this year into verticals.
And the reason we did that is
customers no longer want to talk to us
about speeds and feeds of how fast my database goes.
They want to actually talk about business outcomes.
Hey, how do I solve for demand forecasting?
You know, how do I fix my supply chain issues?
That's how we're aligning with Infosys so well.
Is they've been doing this for a long time.
Candidly, we haven't.
And so we need their help on getting us
to the kind of next level of the sales motion
and talking to our customers
on solving these business challenges.
>> In terms of that next level.
So now question for you,
where are the customer conversations happening
at what level?
I mean, we've seen such dramatic changes in the market
in the last couple years
now we're dealing with inflation, rising interest rates,
Ukraine, are you seeing the conversations
in terms of building data platforms rising up the C-suite
as every company recognizes,
we're going to be a data company
we're not going to be in business.
>> Absolutely.
And I think all the macroeconomic forces
that you talked about
that's working on the enterprises globally,
is actually leading them to think about
how to future prove their business models, right?
And there are tons of learning
that they've hired in the last two to three years
in digitizing, in embracing more digital models.
The conversations with the customers
have really pivoted towards business outcome.
It is a C-suite conversation.
It is no longer just an incremental change
for the companies.
They recognize that data has been touted
as a strategic asset for a long time
but I think it's taking a purpose and a meaning
as to what it does for the customers.
The conversations are around industrial verticals,
what are the specific challenges and opportunities
that the enterprises have?
And how you realize those
and this cuts across multiple different layers.
We were talking about how you democratize data,
which in our point of view is absolute must
in terms of putting a foundation that doesn't take
super specialized people to be able to run every operation
and every bit of data that you process.
We have invested in building autonomous data and AI estate
that can process data as it comes in
without any manual intervention
and take it all the way to consumption.
But also investing in those industry solutions.
Along with Snowflake, we launched the healthcare
and life sciences solution.
We launched the Omnichannel for retail and CPG.
And these are great examples of how Snowflake Foundation
enables democratization on one side,
but also help solve business problems.
In fact, with Snowflake, we have a very special partnership
because our point of view on data economy
is about how you connect with the network partners
externally.
And Snowflake brings native capabilities on this.
We leverage that to drive exchanges for our customers.
And one of the services company in the recycling business,
we are actually building an exchange
which will allow the data points
from multiple different sources and partners
to come together so they have a better understanding
of their customers, their operations, the field operations,
and things like that.
>> So they're building a data ecosystem.
>> Yes, right.
>> Is it a two-sided marketplace where you guys are observers
and providing the technology and the process, guidance?
What's your role in that?
>> Yeah, so we are seeing that evolution come in two stages,
maybe even more.
Customers are comfortable building an ecosystem
that's kind of private for them,
which means that they know who they're sharing data with.
They know what the data is getting used for.
And how do you really put governance on this?
So that on one side you can trust it,
and on the other side there's a good use of that data
and not compromise on data quality or privacy
and some of the other regulations.
But we do see this opening up
to the two-sided marketplaces as well.
Some of the industries lend themselves extremely well
for that kind of play.
We have seen that happening in trading area.
We've seen that happen in the credit checks
and things like that
which are usually open for those kind of ecosystem,
but the conversations and the programs
are really leading towards that in the market.
>> You know, Lisa, one of the things I wrote about
this weekend is I was excited to come to Snowflake Summit
and see one of the thesis I have
is that we're going to move, not just beyond analytics,
including analytics, but also building data products
that can be monetized.
And I'm hoping we're going to see some of that here.
Are you seeing that Chris in the customers?
>> It's a great question, Dave.
So we have, I just thought of it as he was talking about it,
we have a customer who's a very large customer of ours
who's in the financial services space
and they handle roughly 40% of the credit card transactions
that happen in the US.
And they're coming to us and saying,
they want to go from zero in data business today
to a $2 billion business over the next five years.
And they're leaning on us to help them do that.
And one of the things that's exciting for me is
they're coming to us, not saying, "Hey, how do you do it?"
They're saying,
"Hey, we want to build a consumption model
on top of Snowflake.
And we want to use you as the delivery mechanism
and the billing mechanism
to help us actually monetize that data."
So, yes.
The answer is, I used to sell to chief data officers
and CIOs.
Now I'm talking to VPs of sales
and I'm talking to chief operating officers
and I'm talking to CEOs about how do we actually
create a new revenue stream?
And that's just, I mean it's exhilarating
to have those conversations.
>> That's data products.
So they don't have to worry about the infrastructure
that comes from the cloud,
they don't have to worry about the governance
as Sunil was saying.
>> Just put it in Snowflake.
Just put it in Snowflake.
>> So I call it a super cloud
it's kind of a funny little tongue in cheek,
but it's happening.
It's this layer,
that's not just multiple clouds.
You see a lot of your quote on quote competitors,
adjacent competitors saying,
"Hey, we're now running in Google or we're running in Azure,
or we've been running in AWS."
This is different.
>> This is different. >> Isn't it?
It's a cloud that floats above
the infrastructure of the hyperscalers.
And that's a new era, I think.
>> Yeah, it's a new era.
I think the hyperscalers want to keep us as a data warehouse
and we're not.
The customers are not letting 'em.
So, I think that's where Infosys kind of saw the light
early on, and they were our innovation partner of the year,
this past year, and they're helping us
and our customers innovate.
>> But you're uniquely qualified to do that
where it's I don't think it's the hyperscalers agenda.
At least, I never say never with the hyperscalers,
but yeah they have focus on providing infrastructure
and yeah they have databases and other tools,
but that cross cloud, that continuum,
to your point, talking to VPs of sales
and how do you generate revenue,
that maybe is a conversation that they have,
but not explicitly as to how to actually do it
in a data cloud.
>> That's right.
And those are the fun conversations
because you're saying, "Hey, we can actually
create a new revenue stream."
And how can we actually help solve
our joint customers problems?
So, yes, it is.
>> Well, and that's competitive differentiation
for businesses.
I mean, these days, as I mentioned
every company has to be a data company.
If they're not,
they're probably not going to be around much longer.
They've got to be able to leverage a data platform
like Snowflake to find insights, be able to act on them
and create value, new services, new products,
to stay competitive, to stay ahead of the competition.
That's no longer a nice to have, right?
>> A hundred percent.
I mean, I think they're all scared.
I mean, like if you look in the financial services space,
they look at some of the Fintechs as the giant,
800 pound gorillas, look at the small Fintechs
as huge threats to their business.
And, they're coming to us and saying,
"How can we innovate our business now?"
And they're looking at us as the innovator
and they're looking at Infosys to help them do that.
So I think these are incredible times.
>> So the narrative on Wall Street, of course,
this past earning season was consumption
and who has best visibility.
And they were able to,
Snowflake had a couple of large customers
dial down consumption, some consumer phasing.
Here's the thing.
If you're selling a data product
for more than it cost you to make,
if you dial down consumption in the future,
you're going to dial down revenue.
So, it's going to become less and less discretionary over time.
And that to me is the next era that's really exciting.
>> The key there is understanding the unit of measure.
I think that's the number one question
that we get from customers is,
what is the unit of measure that we care
about that we want to monetize?
'Cause to your point, if it costs you more to
make the product, you're not going to sell it.
Right?
And, so I think that those are the things,
that the energy that we're spending with customers today
is advising them, jointly advising them,
on how to actually monetize
the specific unit of measure that they care about.
>> Because when they get the Amazon Bill
or the Snowflake Bill, the CFO starts knocking the door,
the answer has to be,
well look at all the revenue that we generated
and all the operating profit
and the free cash flow that we drove.
And then it's like, oh, I get it.
Keep doing it.
>> Well, if I'm going on sales calls with the VP of sales
and their sales team, fantastic, right.
I'm helping them generate revenue, right.
That's a great conversation.
>> New dynamic.
>> And then I think the adoption
is really driven through the value
that they can drive in their ecosystem.
Data products are similar to products and services
that these companies sell.
And if you're embedding data insights or AI
into your product services,
that makes you that much more competitive in the market
and drive value for your stakeholders.
And that's essentially the future business model
that we are talking about on one side.
The other one is the agility.
Things aren't remaining constant,
they're constantly changing.
And we talked about some of those forces earlier.
All of this is changing, the landscape is changing,
the needs in the economy and things like that,
and how you adapt to those kind of models in the future
and pivot it on data capabilities
that lets you identify new opportunities
and create new value.
>> Speaking of creating new value.
Last question guys, before we wrap.
What's the go to market approach here
between the two companies?
Where can customers go to get engaged?
I imagine both sides?
>> Yeah, I mean the way that partnership looks good to me
is sell with co-selling.
So, I think, we look at developing joint solutions
with Infosys, they've done a wonderful job
of leaning into our partnerships.
So, Sunil and I have a regular cadence
where we talk every quarter
and our sales teams and our partner teams
are all leaning in on co-selling.
I don't know if you have anything to add.
>> Absolutely.
We proactively identify the opportunities for our customers.
And we work together at all levels between the two companies
to be able to bring a cohesive solution
and a proposition for the customer
and really help them understand
what is it that they can get to
and how you get that journey actually executed.
And it's a partnership that works very seamlessly
through that entire process.
Not just upstream when we are selling
but also downstream when we are executing.
>> Chris: Yes.
>> And we've had tremendous success together
and look forward to more.
>> Congratulations on that success guys.
Thank you so much for coming in,
talking about new possibilities with data and AI
and sharing some of the impact
that the technologies are making.
We appreciate your insights.
>> Thank you. >> Absolutely.
>> Thank you. Thank you so much.
>> For our guests and Dave Vellante.
I'm Lisa Martin.
You're watching theCUBE live in Las Vegas
from Snowflake Summit 22.
We're back after the keynote with more breaking news.
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