(bright classical music)
>> Hi, I'm Peter Burris
and welcome to another CUBE Conversation
from our studios here in Palo Alto, California.
We've got another great conversation today,
specifically we're going to talk about some of the trends
and changes in data catalogs,
which were emerging as a crucial technology to advance
data-driven business on a global scale.
And to do that, we've got Alation here,
specifically Stephanie McReynolds who's the Vice-President
of Marketing at Alation.
Stephanie, welcome back to theCUBE.
>> Thank you, it's great to be here again.
>> So Stephanie, before we get into this very important
topic of the increasing, obviously role or connection
between knowing what your data is, knowing where it is,
and business outcomes in a data-driven business world,
let's talk about Alation.
What's the update?
>> Yeah, so we just celebrated, yesterday in fact,
the sixth anniversary of incorporation of the company.
And upon, reflecting on some of the milestones that
we've seen over those six years,
one of the exciting developments is we went from
initially about seven production implementations
a couple years after we were founded,
to now over a hundred organizations that are using Alation.
And in those organizations over the last couple of years,
we've seen many organizations move from
hundreds of users, to now thousands of users.
An organization like Scout24 has 70 percent
of the company as self-servicing analytics users
and a significant portion of those users now using Alation.
So we're seeing companies in Europe like Scout24
who's in Germany.
Companies like Pfizer in the United States.
Munich Reinsurance in the financial services industry.
Also hit about 2000 users of Alation,
and so it's exciting to look at our origins
with eBay as our very first customer, who's now up to
about 3000 users.
And then these more recent companies adopt Alation
all of them now getting to a point where they really
have a large population that's using a data catalog
to drive self-service analytics and business outcomes
out of those self-serving analytics.
>> So a hundred first-rate brands as users,
it's international expansion.
Sounds like Alation's really going places.
What I want to do though, is I want to talk a little bit
about some of the outcomes that these companies
are starting to achieve.
Now we have been on the record here at circling the angle
with theCUBE wiki bomb for quite some time,
trying to draw a relationship between business,
digital business, and the role that data plays.
Digital business transformation, in many respects,
is about how you evolve the role the data plays
in your business to become more data-driven.
It's hard to do without knowing what your data is,
where it is, and having some notion of how it's
being used in a verified trusted way.
How are you seeing your company's start to tie
the use of catalogs to some of these outcomes?
What kind of outcomes are folks trying to achieve first off?
>> Yeah, you're right.
Just basic table stakes for turning an organization into
an organization that relies on data-driven decision-making
rather than intuitive-decision making requires an inventory.
And so that's table stakes for any catalog,
and you see a number of vendors out there
providing data inventories.
But what I think is exciting with the customers that
we work with, is they are really undertaking
transformative change, not just in the tooling and
technology their company uses, but also
in the organizational structure, and data literacy programs,
and driving towards real business impact,
and real business outcomes.
An example of an Alation customer, who's been talking
recently about outcomes, is Pfizer.
Pfizer was covered in
a Wall Street Journal article, recently.
Also was speaking at TABLO Conference, about
how they're using a combination of the Alation data
catalog with TABLO on the front end, and a data science
platform called Data IQ, in an
integrated analytics workbench that is helping them
with new drug discovery.
And so, for populations of ill individuals,
who may have a rare form of heart disease, they're
now able to use machine learning and algorithms that
are informed by the data catalog to catch one percent,
two percent of heart disease patients
who have a slight deviation from the norm, and can
deliver drugs appropriately to that population.
Another example of the business outcome would be with
an insurance company;
very different industry, right?
But, Munich Reinsurance is a huge global reinsurance
company, so you think about hurricanes or the fires
we had here in the United States,
they actually support first line insurers
by reinsuring them.
They're also founding new business units
for new types of risks in the market.
An example would be a factory
that is fully controlled by robots.
Think about the risks of having that factory
be taken over by hackers in the middle of the night,
where there's not a lot of employees on the floor.
Munich Reinsurance is leveraging the data catalog
as a collaboration platform between actuaries and
individuals that are knowledgeable in the business
to define what are the data products that could support
an entirely new business units, like for cyber crimes.
And investing in those business units based on the
innovation they're doing using the data catalog
as a collaboration platform.
So these are two great examples of organizations that,
a couple years ago started with a data catalog, but
have driven so many more initiatives than just analyst
productivity off of that implementation.
>> Oh, those are great outcomes.
One of them talking about robots in the factory,
automated factory, one thing, if they went haywire,
would make for some interesting viral video.
(gently laughs)
>> That's right. That's right.
>> But coming back, but the reason I say that is because
in many respects, these practices, these relations with
the outcomes, the outcomes are the real complex thing.
You talked about becoming more familiar with data,
using data differently, becoming more data driven.
That requires some pretty significant organizational change.
And it seems to me, and I'm querying you on this,
that the bringing together these users to share their
stories about how to achieve these data driven outcomes,
made more productive by catalogs and related technologies.
Communities must start to be forming.
Are you seeing communities form around achieving these
outcomes and utilizing these types of technologies to
accelerate the business change?
>> So what's really interesting at an organization like
Munich Reinsurance or at Pfizer, is there's an
internal community that is using the data catalog as a
collaboration platform and as kind of a social networking
platform for the data nerds.
So if I am a brand new user of self-service analytics,
I may be a product manager who doesn't know how to write
a sequel query yet.
Who doesn't know how to go and wrangle my own data.
>> Yeah, may never want to.
(playfully laughs)
>> May never want to.
May never want to.
Who may not know how to go and validate data
for quality or consistency.
I can now go to the data catalog to find trusted resources
of data assets, be that a dashboard to report that's
already been written or be that raw data that someone else
has certified, or just has used in the past.
So we're seeing this social influence happen within
companies that are using data catalogs, where they can see
for the data catalog pages, who's used, who's validated
this data set so that I now trust the data.
And then, what we've seen happen, just within the last year
and-a-half or so, is these organizations, the sponsors of
the data of these organizations, are starting to share
best practices naturally with one another, and saying, hey
>> Across organizations.
And so there has been a demand for Alation to get out
into the market and help catalyze the creation
of communities across different organizations.
We kicked off, within the last two months, a series of
meetings that we've called RevAlation.
>> R-E-V-A-L
>> That's right
>> A-T-I-O-N
>> R-E-V-A-L-A-T-I-O-N
And the thing behind the name is,
if you can start to share best practices in terms of how
you create a data-driven culture across organizations,
you can begin to really get breakthrough speed, right?
In making this transformation to a data-driven organization.
And so, I think what's interesting at the RevAlation events,
is folks are not talking just about how they're using
the tool, how they're using technology.
They're actually talking about how do we improve the data
literacy of our organizations and what are the programs
in place that leverage, maybe the data catalog, to do that.
And so they're starting to really think about, how does,
not just the technical architecture and the tooling change
in their organizations, but how do we close this gap
between having access to data and trusting the data
and getting folks who maybe aren't, too familiar with the
technical aspects of the data supply chain.
How do we make them comfortable in moving away from
intuitive decisions to data-driven decisions?
>> Yeah, so the outcome really is not just the application
of the tool, it's the new behaviors in the business that
are associated with data-driven.
But to do that, you still have to gain insight and
understand what kinds of practices are best used
with the tool itself.
>> That's right.
>> So it's got to be a combination.
But, you know, Alation has been, if I can say this.
Alation's been on this path for a while.
Not too long ago, you came on theCUBE
and you talked about trust check.
>> Right.
>> Which was an effort to establish conventions
and standards for how data
could be verified and validated so that it would be
easy to use, so that someone could use the data and
be certain that it is what it is, without necessarily
having to understand the data.
Something that could be very good for, for example, for
folks who are very focused on the outcome, and not
focused on the science of the data associated with it.
>> That's right.
>> So, is this part of, it's RevAlation, it's trust check.
Is this part of the journey you're on to try to get people
to see this relation between data-driven business and
knowing more about your data?
>> It absolutely is.
It's a journey to get organizations to understand what
is the power that they have internally, within this data.
And close the gap on, which is in part organizational,
but in part for individuals user's psychological and how
do you get to a trusted decision.
And so, you'll continue to see us invest in features like
trust check that highlight how technology can make
recommendations;
can help validate and verify what the
experts in the organization know
and propagate that more widely.
And then you'll also see us share more best practices about
how do you start to create the right organizational change,
and how do you start to impact the psychology of fear
that we've had in many organizations around data.
And I think that's where Alation is uniquely placed, because
we have the highest number of data catalog customers of
any other vendor I'm familiar with in this space.
And we also have a unique design approach.
When we go into organizations and talk about adopting a
data catalog, it's as much about, how do our products
support psychological comfort with data as well as,
how do they support the actual workflow of getting
that query completed, or getting that data certified.
And so I think we've taken a bit of a unique approach
to the market from the beginning where we're really
designing holistically.
We're not just, how do you execute a software program
that supports workflow?
But how do you start to think about how the data
consumer actually adopts that best practices
and starts to think differently about how they use data
in a more confident way?
>> Well I think the first time that you and I talked
in theCUBE was probably 2016, and I was struck by the
degree to which Alation as a tool, and the language that you
used in describing it was clearly designed for human beings
to use it.
>> Right.
>> As opposed to for data.
And I think that, that is a unique proposition, because
at the end of the day, the goal here,
is to have people use data to achieve outcomes
and not just to do a better job of managing data.
>> And that doesn't mean that,
I mean we have a ton of machine learning,
>> Sure.
>> And AI in the products.
That doesn't take away from the power of those algorithms
to speed up human work and human behavior.
But we really believe that the algorithms need to compliment
human input and that there should be a human in the loop
with decision-making.
And then the algorithms propagate the knowledge that we
have of experts in the organization.
And that's where you get the real breakthrough business
outcomes, when you can take input from a lot of different
human perspectives and optimize an outcome by using
technology as a support structure to help that.
>> In a way that's familiar and natural and easy for others
in your organization.
>> That's right.
That seems, you know, if you go back to.
>> It makes sense.
>> When we were all introduced to Google
it was a little bit of an odd thing to go ask Google
questions and get results back from the internet.
We see data evolving in the same way.
Alation is the Google for your data in your organization.
At some point it'll be very natural to say,
'Hey Alation, what happened with revenue last month?'
And Alation will come back with an answer.
So I think that, that future is in sight,
where it's very easy to use data.
You know you're getting trusted responses.
You know that they're accurate because there's either a
certification program in place that the technology supports,
or there's a social network that's bubbling this information
up to the top, that is a trusted source.
And so, that evolution in data needs to happen for our
organizations to broadly see analytic driven outcomes.
Just as in our consumer or personal life,
Google had to show us a new way to evolving, you know,
to a kind of answering machine on the internet.
>> Excellent.
Stephanie McReynolds, Vice-President of Marketing Alation,
talked to us about building communities,
to become more of a, to achieve data-driven outcomes,
utilizing data catalog technology.
Stephanie, thanks very much for being here.
>> Thanks for inviting me.
>> And once again, I'm Peter Burris,
and this has been another CUBE Conversation until next time.
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