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>> Good morning.
Welcome back to theCube, the leader in live tech coverage
covering day three of Snowflake Summit.
This is actually their day four, our day three.
Lisa Martin, Dave Velante here.
We've had some awesome conversations, as we always do.
We're going to be teaching you
how to become a query boss, Dave.
>> Query's really interesting, right?
'Cause we've been talking all week
about how the Snowflake has many different query options.
They started with SQL, added data frames,
and now it's this search with Niva
and NLP and stuff they're doing with Nvidia.
So it's really interesting
to see the expansion of the platform.
>> It is.
Becoming a query boss.
We're going to be learning how to do that.
Jacques Nadeau, one of our alumni joined us.
He's now the CEO and co-founder of Sundeck.
Jacques, great to have you on the program.
>> Yeah, thanks for having me.
I really appreciate it.
>> Talk a little bit about Sundeck and Query engineering.
I'd love to know about the name and about flow, your mascot.
>> Yeah, absolutely.
So, Sundeck is a relatively new company.
We started a little over a year ago.
We actually just launched.
Our product came out of stealth about four weeks ago.
And we're focused on query engineering.
And query engineering is about
really the art and science of getting your queries
to work better for your organization.
And there's a lot of different ways that
that can impact an organization.
So, one of the simplest ways that people understand is
is that like, you want to make sure
that for each query that's running,
you're getting the best efficient use of resources, right?
And so, trying to figure out how you can use,
in the case of Snowflake, warehouses more effectively,
how you can use different kinds of patterns
inside of Snowflake effectively.
And that's a pretty obvious one with query engineering.
What people don't necessarily initially realize is
another thing that query engineering can do for them is
that in organizations, especially data driven organizations,
you have larger and larger communities of users
actually interacting with data.
And so, while there are a group of users
that may be highly sophisticated in their use of data,
there's a lot of users where data interaction is only
a very small part of their job.
And these users often make mistakes.
And so, there are tools,
like cataloging tools that help you to try to remember
how to work with data effectively.
Unfortunately, those are kind of offline.
And so if you make a mistake,
the biggest risk you have for an organization is
that these people interact with the data,
they make a mistake of how to access the data,
and then they take that to be fact
and start making conclusions
from the business based on those incorrect assumptions.
And so, query engineering actually operates
at the layer, right?
When the query hits the data cloud and watches those queries
and actually can intercede and say,
"Hey, you know what?
You actually didn't do this correctly
and so, why don't you correct what you're doing?"
Or potentially automatically correct what they're doing
so they don't come to the wrong conclusion
and then impact the business in an impact in a poor way.
>> One, the question is that jumping into my mind is,
isn't Gen AI going to take care of a lot of this?
Or are you Gen AI?
>> So, it's a great question.
So the most, the biggest pattern you see today, right?
Is you see LLMs and Gen AI,
basically create lots of additional queries.
Okay?
And so what you're doing is you're actually
lowering the bar of sophistication of users
to be able to access the data.
>> Dave: Making the problem worse.
>> Yeah, so it's actually making the problem worse
is you're making it easier for people to just generate
like really, really large queries that are going to be
both inefficient and also like,
how do you know that Gen AI got this stuff,
the patterns correct.
Right?
And so, that's great.
It's actually helpful for us.
We actually think it's very exciting.
>> Is that in part why you started the company
as you sort of saw this happening and said,
"Okay, this is going to be even a bigger problem
than it is today."
>> Well, so it's a couple things, right?
So one was, is that over the last several years,
I've worked with a lot of large data organizations
and what we started to see is actually organizations build
bespoke solutions to solve this problem.
And so, especially in financial services and healthcare,
we've seen a number of different companies
who try to cobble something together
to solve these problems.
Now for, just like any kind of internal technology,
they're underfunded.
They're poorly, not poorly built
but they just don't have enough resources
and time to really make them successful.
And so, they solve the narrowest possible way of solving
this problem.
And so that was the first pattern.
But then the second pattern is exactly that,
which is that all we're seeing is larger
and larger communities of people working with data.
And the larger that community is,
the more there are people who are less sophisticated
and less day-to-day working with that data.
>> Are there technologies that Sundeck is replacing?
>> Really, no.
We're creating a new category.
And so the only technologies I'd say we're replacing are
those situations where people have built bespoke solutions
to solve this problem.
So we're excited about creating a new category.
It's challenging to always create a new category
but we find it to be also really rewarding.
We've been here the last few days
at the summit on the floor and the interaction
and response has been just marvelous,
not only from people who use Snowflake
but a lot of the team at Snowflake themselves, right?
So that AEs and SEs coming
from Snowflake are often saying like,
"Man, I hear this every day and it's great
that you guys have a solution to help us out."
>> So when I talk about, again,
we've been talking all week about the numerous query methods
that Snowflake is supporting.
I presume on the one hand
that makes the problem worse, right?
'Cause you've got a lot of different people using analysts
who are doing SQL, they're doing Python, data frames.
That's how Python programmers talk to data.
>> Yep. >> They're probably pretty good
at queries but maybe not, I don't know.
And then like you said, NLP just makes this a nightmare.
>> Yeah, yeah, yeah.
No, so it's not only people
who are writing queries themselves, right?
It's all the tools that are generating queries, right?
So like, most organizations have 10, 20, 50 BI
and other kinds of technologies
that are accessing their data cloud
and all of those things, people can make mistakes
in those as well, right?
And so it's not just about like, is it efficient or not.
>> Dave: Right.
>> Like it's about like,
"Oh, am I doing this pattern correctly
or is there a way I can get this much more faster?"
Right?
Or more up to date, right?
Like, there's always this question of like,
how old is this data
and is it going to be the best version of what I'm getting?
>> So what are you doing with Snowflake
and where do you fit into that whole value chain?
>> Yeah, yeah, yeah.
So the pattern is we basically sit
in front of the data cloud and can pass query through
but then also intercede
and the focus is really around data engineers.
We recognize data engineers as basically
the greatest new collection of creative people,
sort of in this data ecosystem, right?
And we see a lot of that exciting creativity
in the context of DBT and the rise of analytics engineering.
And so we're working with those same users in this context
and we engage in a couple of different ways.
So the first is, is that, as I said,
we sit in front of the data cloud
and allow you to do this interception.
But the second thing that we actually announced here
at the summit and we're our launch partner
with Snowflake on, is a new Native App.
So we built a Native App called Op Center for Snowflake.
And this came out of primarily our own experiences
with challenges around understanding consumption of
these technologies, elastic computing technologies.
And so, we built this application.
We started by building stuff for our own purposes
and then realized that every customer we talked to
was struggling with the same kind of thing.
And so, I've worked in open source
for the last 20 years and I'm very passionate
about building communities
where there's a common sort of goal and need,
but it's not really something
that makes sense to monetize.
And so, so we actually not only created the
the Op Center project as a free project inside
the marketplace, but we also made it available on GitHub.
So not only can people take advantage of that, use it,
they can also contribute back to it and we can extend and so
that people spend less time thinking on a day-to-day basis
about the consumption challenges of working
with something like Snowflake.
>> What was it like building a Native App with Snowflake?
It's a great question.
It's rewarding and it's rewarding because
as a small company,
it's hard to sell to big companies, right?
We're new.
How much trust do you have with a small company?
And what Native Apps gives us is the ability
to basically provide something
to a very, very large enterprise in a way
that they're very secure.
So Native App runs inside of their Snowflake account,
no data leaves their Snowflake account.
We don't have access to any of that data.
And so it allows us to establish
a substantial amount of trust as a small organization
with these large organizations.
>> So, what was it like raising money in the past year?
>> Well, we were very lucky.
I guess that's what I would say.
So we actually raised. >> And trust.
>> So some of the companies in this space,
between the time that we signed our term sheet
and got our money, had lost 50% of their valuation.
So we raised at exactly the right moment,
I guess I would say, having conversations more recently
I think it would be much harder.
>> Okay.
And so you've raised, is it correct,
you've raised about 20 million.
>> That's right. >> Is that right?
>> Jacques: Yeah.
>> And I presume you hire an engineers.
>> Yep. >> It's really
where you're focused on.
>> Yeah. >> And headcount today or.
>> Jacques: Yeah, we're about 15 right now.
>> Okay, so really focused.
So, you got plenty of capital, at least for now.
>> Yeah, absolutely.
Yeah, no, we got, we got five years of runway right now.
You're spending it on promotion at this point.
>> Yes. >> So, okay.
So that partnering with a Snowflake is,
helps elongate that runway as well.
>> Absolutely.
It accelerates our ability to do things, right?
Like, obviously they've got people out there
in the field everywhere, right?
And so, if we can give them a solution,
so it was one of the hypotheses of the company is that,
I had worked at Dremio before and one of the things
I saw was is that people at the edge,
they're actually trying to get deals done
and try to solve customer problems.
They need more power tools, they need more tools to actually
be able to change what's going on with the data systems
they're working with, right?
Like, you can open up a feature request
to try to enhance something, but when you're talking about
a massive powerful platform like Snowflake
It's going to take some time to enhance it
and it's probably going to be a fairly narrow version of that.
And so if you can give both data engineers and what SEs are
which is effectively like, part-time data engineers
to help their customers some kind of capability
to solve these problems,
that can work very, very well.
>> Are you hitching your wagon to Snowflake
and so exclusively, or not necessarily?
You are.
>> For now, we're entirely focused on Snowflake.
>> Dave: Yeah.
>> Like, who knows what the future will bring.
>> Yeah, but that's smart start, get a foot in the door and.
>> Yeah, it's an awesome platform
and has a huge amount of option.
>> What are some of the opportunities that you see
in the data cloud the next year, three, four years out?
>> Well, the most exciting thing about Snowflake is
this opportunity to push into what is the data cloud
and what can that become, right?
And so, I actually think a lot about Salesforce
in this context, right?
Like Salesforce went from an application to a place
where huge amounts of applications run inside of
that ecosystem.
And it was because they had sales data, right?
They had sales data and everybody wants
to build applications around sales data.
Well, Snowflake is just, 10x that, right?
Because there's all the data is inside of Snowflake.
And so, the thing that they have as an opportunity is
to be able to create that same kind of ecosystem,
but about around all the different sort of sub industries
that are working with Snowflake data.
And so, I think that that's the exciting part.
Now, becoming a developer company, right?
Which has historically been
what I would say is more of
a data engineering analyst country company.
I think that that's going to take some time
but I think that that's the most exciting opportunity.
>> So you're developing in Snow Park, is that right?
>> So, some of it's in Snow Park, but it's also
in the Native App framework, which in part is Snow Park.
>> Okay, so what's that been like?
What's that experience been like?
How's the maturity, as a customer.
>> Yeah, I would say, well, it was public preview started
at Summit, so it's young.
I would say that definitely we learned a lot along the way
and you had some bugs and whatnot
but it was also very pleasant.
Like it's built for people who work with databases
and so, it worked well for that.
I think that one of the challenges that we saw is
we wanted to customize things more
and really enhance the user experience.
And right now it's a little bit constrained in that respect.
And so, the benefits far outweighed the challenges
that we saw with it being that you can get
into these larger organizations without having to
go through the same cybersecurity efforts
that you potentially always would.
But there is definitely a lot of things
that can be taken to the next level as well.
>> So, the hardcore techies are going to want more
sort of hands-on access to tooling.
>> Yeah.
>> How does that affect Snowflake's promise in your view?
I mean, they have to be careful about their governance
and their security and that hot is what takes forever
for that's why we still don't see Uni store
in public previews because it's hard.
>> It is very hard.
And it's an excellent question, right?
So they launched container services in a private preview
at Summit where you can run arbitrary code, right?
And so, what they did with Native Apps is they
basically said you can't get to the network.
And they made that a very, very tight system
and that keeps your data in, right?
But the moment you give people arbitrary code running
inside of Snowflake accounts,
it's going to be a different level of challenge, right?
Because of exactly what you said, which is like,
if you let them have arbitrary code,
they can also go out to the network and it can see the data.
You have to really think about how that is different
than running outside the Snowflake cloud.
And so I think that's going to be the challenge is
like providing that substantial amount of flexibility.
Right?
Because developers have a lot of tools
that they want to work with today, right?
Python and Spark, you can, or Python and Java
and JavaScript are the three options you have
inside of the sort of like the closest part
to the data system right now.
But developers like a lot of other languages.
And so, yes, you can run these things
and kind of container services,
but I think that that's going to be the thing
that's going to be really challenging is to figure out
what's the right balance between the governance
and the flexibility of the developer wants.
>> And they'll add more and more of those over time
but they've got to make sure it fits into the framework.
What are the similarities and differences with
this sort of app store in the iPhone model?
>> Well, I think that the similarities are is
it feels very much the same.
Like you go into the app store and you click something.
I think that one of the really big differences
and then what we see is a little bit of a challenge is
that it is patterned around administrators, right?
So like when everybody's got their own phone,
they can install stuff on their own phone.
Sure, there might be like corporate mandate
in some of your phone,
but you can also install your own apps onto your phone.
And right now, you don't have the ability for, say,
a random analyst or data engineer
to install apps inside of Snowflake.
So I'd say that that's pretty much the biggest difference.
That and then then sort of
like the constrained flexibility≥
>> Do you think that will evolve as the ecosystem grows
and demands that, or is that antithetical
to that whole promise of governance and security,
or don't know yet?
>> I think it's a good question, right?
Because I mean, Snowflake has a really rich R back model
for security, right?
And so, as long as you don't violate that model
why couldn't others install the apps.
So I think that it could go there.
I'm not sure that it's a natural tendency
for people to go there, right?
Like, one of the things that have traditionally been true of
data systems is, is that administrators have
the ability to create things
that many other users don't have the ability to do.
And so I think that that may be something
that they'll have to figure out how they sort of,
navigate that.
>> So what are your big milestones?
You're at the board, here's what we're doing, folks,
and boom, boom boom.
>> Yeah, yeah, yeah.
Well, I mean, we just hit a couple of them, right?
We just launched our first, our SaaS product four weeks ago
and we launched the Native App here.
From here, it's just making customers successful
for their foreseeable future.
Like, that's all we're focused on right now.
And really, we believe that something
so one of the things I've seen
with query engineers is generally
because it is bespoke solutions,
is often limited to larger, larger organizations.
Others can't afford to put a team of developers
against this problem.
And so we want to make it broadly available, right?
And so any data-driven organization is going to be more
and more struggling with this challenge of like
how I make these queries work the best for me.
>> So you're not worried about go
to market fit at this point.
You're trying to nail product market fit.
Once you nail that, in a way,
it will take care of itself with Snowflake.
'Cause that's a really smart way to start.
And then who knows, the tam can expand from there.
>> Absolutely, yeah.
>> Awesome.
>> And what customers are you working with?
Don't have to mention my name,
that you're really excited about
in terms of really getting the value.
>> Yeah, we've got really good engagement
with actually a number of
the largest financial services customers.
So we've got some good engagement there as well
as a number of people in retail.
And so both of those are looking really, really positive.
>> Awesome.
Jacques, thanks so much for joining us on theCube,
talking to us about Sundeck.
sundeck.io, what you're doing with Snowflake
and how customers are really can become query bosses
as your website says.
I love that, by the way.
>> Awesome.
Thanks so much for your time, really appreciate it.
>> Great to have you.
We want to thank you for watching.
For our guests and for Dave Velante, I'm Lisa Martin.
Up next, our final segment for Snowflake Summit '23
with Cube alum and Snowflake CMO Denise Persson.
She's going to be breaking down the event,
its differentiators, how they will extend this event
past the four days.
And she's going to be dropping some news
about next year's summit.
You can only find that here on theCube.
Catch all of our content on thecube.net
and analysis and editorial on siliconangle.com
and we'll see you in a minute.
You're watching theCube, the leader in live tech coverage.
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