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>> Hi, I'm Peter Burris.
Welcome again to another CUBE Conversation
from our wonderful studios in Palo Alto, California.
Great conversation today:
Branching out into the world of data governance.
Lot of things going in the industry around data
and what does it mean for digital business
and how do we treat data increasingly as an asset
and that obviously raises a lot of questions
about how we govern those assets,
improve their value, share them appropriately,
same time privatizing
and make sure that they aren't corrupted.
And to have this conversation we've got two great guests.
First off we've got Kelle O'Neal,
who's the CEO of First San Francisco Partners,
which is an information management consultancy
here in the Bay area,
and Satyen Sangani, welcome back to theCUBE,
CEO of Alation.
Welcome.
>> Thank you. >> Thank you.
>> So let's get started.
I kind of said in the preamble that this notion
of data governance becomes especially acute,
especially important, because we're now trying
to treat data as an asset.
So we're not governing the resources that manage data.
We're actually trying to
govern data itself, utilizing resources.
So, Satyen, why don't we start with you.
What does data governance mean
from a tool and process standpoint?
And then Kelle, I ask you,
and let's go deeper into that process part.
>> So there's lots of different definitions
of data governance that
a wide variety of experts have put out
and I'm not sure that I want to put
a new definition in the debate.
Very generically, it's a set of processes
that institutions use to manage the data
that's at their disposal.
And if you think about that generically,
in terms of where the problem is broadly stated,
how do I manage my information and the consumption,
and the production and the storage of that information?
That is a super hard problem to deal with
when you have hundreds of thousands of data sources,
potentially millions of different datasets
and thousands of people are constantly consuming
that information and limited resources.
So the process of data governance,
now in a world, to your point, where every business
is trying to become a digital business
and where the monetization of data
is a huge part of that business,
is the fundamental problem, right.
How do we have people discover the data?
How do we have people understand
the data that they're seeing?
How do we have people trust the data that they're seeing.
That is the sort of province of data governance
and that is what people are coming to realize today.
>> But we do have tooling now
that is specifically being built, including Alation,
which is a great catalog for performing some of these,
or to facilitate some of these governance activities.
So there's enough of a standard set of definitions
that we actually can put tooling in place,
which means now we can really liberate the power
and the talent of people
to appropriately govern data and use data.
So Kelle, what are you doing with your clients
to help them take the tools for data governance
and turn it into, ideally, a strategic capability
that really drives a digital business forward?
>> Yeah, absolutely, so as a services organization,
we really focus on ensuring that
the people and the process are in place
so that they can take advantage of the technology, right.
So you've got accountability around who has,
who's responsible to ensure that data is of
a certain sort of quality or
a certain sort of standard,
as well as, who has the ability to access
that data and use that data.
And I think one of the things that Satyen brought up,
is there's just this onslaught of data that's coming in.
So if you think about that as a construct,
it's entirely overwhelming.
There's too much data to be able to say
this person owns this data field,
this person defines that data field.
It has to be much more organic.
It has to be much more shared and tools like--
>> Communal. >> Much more communal, yeah.
And so it really is this concept of,
how do we have a certain level of trust in the data
and what does trust mean to the organization
to take advantage of that data
and to use as an asset
and to use it in business context.
And so our services help organizations
to see what that means to them,
to right size that investment,
in the sense of how much effort do we put towards this.
And then also how do we make sure
that those tools are used,
that they are adopted
and then that they're embedded into work processes.
That it's not a standalone repository that never gets used.
>> You know, we had Aaron Kalb on not to long ago
to talk about trust check.
And I know that's one of the things that's
bringing you together
is this notion of
a communal approach
to putting, to imbuing data with trust.
So, let's talk a bit about trust check
and, in particular, how your companies are working together
to accelerate the processes
that you so accurately described.
Satyen, why don't we start with you.
What is trust check and what does it mean for you guys?
>> Yeah, so trust check is a very simple,
it's a very simple capability,
although very complicated to implement.
The idea behind trust check is that
as and when somebody is consuming data,
whether that's in a Salesforce dashboard,
or in a Tableau report,
or conversely even inside of Alation,
that immediately, as they're consuming that information,
they're presented with context around that data
talking about the appropriateness of that data
for the use that they particularly have.
Now, that could be about timeliness of the data.
That could be about the availability of the data.
That could be about the quality of the data.
That could be about the privacy regulations,
or the security surrounding that data.
There are lots of reasons why one might not trust the data,
but often that information is off the side, right.
And often that information is in a place
where the consumer of the data has no awareness
that the policy even exists, much less
where to go get it that information.
And so a trust check is saying:
Look, this notion of governance has to actually be
actionable, immediate and available,
in order for it to be valuable
to the person that's using the information.
>> Yeah, and you might say that also
that it might be trusted in this context,
but not in other contexts,
as well. >> Right.
>> So, how does that inform, or how does that facilitate?
How does that accelerate?
Implementing these processes to make sure
that community use of data in an evidence-based world
are better able to
apply data, use data,
and share information about that data with each other.
>> Yeah, absolutely.
So it provides, number one, just automation right.
So fundamentally, that's a value-add.
It means that it's more available,
it's more shared, it's faster,
and that can
make the governance organization
more relevant to the business,
so that the data is actually
used in more appropriate and higher value way.
So first thing's automation.
And then the second thing is that
as we start to automate, there's this concept
of kind of learning and expanding.
And so being able to leverage a tool
within a service's practice and methodology,
it means that we can kind of start within one area
and to leverage that learning
and extend, and extend, and extend.
Because fundamentally data is pervasive.
Right, it's everywhere.
And which makes governance really intimidating and hard.
So, that idea of focusing,
learning,
doing something well and being agile right,
and growing over time,
a tool really helps you to do that,
because it is a place where people can get focused
for that learning, and then repeat.
Rinse and repeat, rinse and repeat.
>> So in many respects,
it is a reflection of manifestation
of some of these good processes.
>> Absolutely.
>> You guys obviously have an enormous amount
of knowledge about data governance,
about the tooling for data governance,
about where this all goes.
But ultimately a lot of your customers
are still very much in the formative stages
>> Yeah. >> of putting this in place.
So, how are, other than just having them
license Alation's toolkit,
how are you coming together to put in place
services, or training, or something else
to help diffuse your knowledge
into the organization. >> So I just
want to come back to one point that you mentioned
is I think there's been a been a shift in
the tooling marketplace. >> OK.
>> So I wouldn't say that the tooling has not,
that there's never been any tooling to deal with
the problem of data governance.
In fact, I think there's been lots of tooling
that hasn't worked particularly very well.
>> So let me, let me-- >> So, so--
>> Let me put some context on that.
>> Yeah. >> When I say tooling,
>> as I said kind of upfront,
to my mind it's tooling for the resources
that handle the data, not tooling for the data.
But keep going, if I'm wrong I want to hear it.
>> Well no, I think even tooling for
the resources that handle the data
has largely been the province of...
There is this category of software
that one would traditionally describe
in the realm of data stewardship and data governance.
>> OK.
>> And broadly speaking, it allows you to create forms
and to administer workflows with those forms.
Right, so.
So that is a highly unautomated capability,
that focuses very deeply on the process of governance.
>> Right.
>> And so, what a traditional
governance
regime might include,
would be the development of policies
and the enactment of those policies
through a set of people who have
to very manually check the data at their disposal.
It is generally speaking disconnected from the data.
>> Right, when you have small sets of data,
when you have limited quantities of data,
that could be a perfectly fine solution.
When you have a very small set of policies
that you need to interact, or interact with,
because you have to have a set of goals
that are maybe regulatory in nature,
that is an OK thing to go do.
When you have petabytes of data across
hundreds of thousands of datasets,
it's an impossible thing to go do, right?
So I thing that that sort of indentation
that Kelle was referring to,
is born out of this massive volume of data coming up,
where the traditional methods just don't work, right.
>> So you're, >> And--
>> So are you talking about, Satyen,
essentially that we're adding that metadata
directly to the data itself,
and creating trusted objects
that the organization can use
and apply as assets wherever it needs to be applied.
>> So that is exactly the solution.
And the analogy that I think that will better inform
most of the people who are listening to us today,
would be the sort of shift from Yahoo! to Google.
Right, so if you think about Yahoo!.
Yahoo! relied upon every single webmaster
tagging every single web page
to make sure that the search engine knew
which web page to go look up.
That required a whole bunch of trust in your webmasters,
first of all, some of whom are bad actors.
(Kelle laughs)
You may not have those in the stewardship regime
inside of your enterprise. >> Uuuuuhhhmm (laughs)
>> But you could, right.
People have their own perspectives.
And it also required for people
to have enough knowledge to tag things, right.
So you'd have to know what to tag
and that tag would have to be right.
For anybody who's developed a folder system,
you know that those folder systems
are constantly changing, right?
And so then Google comes along and says,
"Look, if we just watch what people
"are doing with this information,
"and we know what people are linking to,
"then we can say, hey what's more valuable?
"What's more useful?
"By watching the behaviors, right?"
And I think that's the sort
of shift of a bottoms-up approach.
Which is different from sort of that
top-down declarative approach,
that's come in the technology for
the governance and virtual link.
>> Got it.
>> And I think that's what people have to understand,
which is the problem's always been there.
But what's happened is the volumes,
and the relevance, and the timeliness of the information
have just been so critical that now,
we have to change the way we do things.
>> So it's more cu-- >> And that's,
what we're working together on.
>> Yeah, absolutely. >> Yeah, it's more cute,
it has scale issues,
but also the underlying technology
has gotten to the point where we can actually do
more automated discovery about how people are using things.
>> Which means you have to change the process,
and the people. >> Right, right.
>> Yeah, yeah.
>> So, let's come back to that question.
What are you guys doing together
to ensure that you can, in fact,
diffuse this knowledge and diffuse these insights
into organizations faster, so they can
pick up on some of these changes better.
>> Yeah, so I'll start? >> Go ahead, yeah please.
>> OK, sure.
So, First San Francisco is taking some of our methodologies
and ensuring that they are right-sized and fit
for the Alation suite of products,
especially the trust check suite of products.
And so, what we're starting with
is the data acquisition process.
And that's important because the supply chain for data
is what has become inordinately complex.
It's no longer primally internally created data,
most data is actually acquired.
And so if we start with that ingestion process,
and the data acquisition process,
it's a huge value both to the customers that are using it,
as well as the mutual organizations, right.
So we're focusing on that as a case.
And then, we'll move on to the concept
of information stewardship itself.
So stewardship across the supply chain,
not just the data acquisition supply chain.
So we are adapting our methodologies,
to be specific and unique to Alation,
to help their existing customer base
and obviously potentially new customers together.
>> Yeah. >> Yeah.
>> So, in a great example of that,
I was just talking to a chief data officer
of a very large financial institution in North America.
You know this individual was contending
with the problem of making good data available to
their business audience for analytical purposes.
Right, to solve exactly this problem.
He said, "We acquire companies all the time,
"we're acquiring companies constantly,
"and we're getting all of this data in,
"and I have to figure out what this data is.
" And do I already have this data in-house?
" Do I have systems that store this sort of data?
" Do I have systems that duplicate the data,
"but incorrectly?
"And, are there multiple of these sets of data
"inside the company that I'm acquiring,
"'cause they have got data duplication
"just like we do?
"And how do we figure all of that out?"
So, this would be a perfect example
where the data acquisition problem
is critical to solve in the process
of being able to create available, useful, governed data.
Right?
And so this would be a perfect example
for the two of our companies to be able to work together,
because we don't speak to
the implementation and the process,
we speak to the technical capability
of simply providing the inventory,
so that somebody can then figure out
what to do with that information.
>> But there are practices that are probably going to do better,
or will generate greater value
out of the Alation toolkit than others would.
>> Absolutely.
>> Yeah, and so in many respects,
we're looking into companies like yours
to help, to find what those practices are,
diffuse them more broadly >> Absolutely.
>> through some package consulting,
and through a really good partnership
that you guys have been working on.
>> Yeah, and because I mean, you know,
I think Larry Ellison's a controversial character, right?
>> Who?
(Kelle and Satyen laugh)
>> But, I'll quietly say that I worked
at Oracle at one point in time.
>> So did I.
(Kelle laughs) >> One of the things
that Larry said is people
when they buy software,
are constantly asking the question of
how do I figure out how to take my
existing business process
and fit it on top of the software that exists out there.
And he's like, "No, that's exactly wrong.
"What people should be doing is
"figuring out what should my business process be
"given the capability that I've got."
And so, we now have a new capability
and we're enabling people to have
more or less superpowers relative
to what they would have had to do
by punting and pecking through every dataset
and tagging it manually.
And what Kelle and First San Francisco
are bringing to the table,
is the ability to have a new process
that will allow them to do that at scale and faster.
So, that's why we're super excited.
>> Excellent, so in data-first world,
data governance becomes more important.
Two thoughts leaders helping to make that happen.
Satyen Sangani, CEO of Alation.
Kelle O'Neal, First San Francisco Partners.
Thanks very much for being on theCUBE.
>> Thank you, thank you. >> Thank you Peter.
>> And once again, this has been a CUBE Conversation
from our Palo Alto studios.
Thank you very much for watching,
until next time.
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