>> From Cambridge, Massachusetts,
it's theCUBE
covering MIT Chief Data Officer
and Information Quality Symposium 2019.
Brought to you by SiliconANGLE Media.
(electric music)
>> Welcome back to
MIT CDOIQ everybody.
You're watching theCUBE.
We go out to the events
and we extract the signal from the noises.
Day 1 of this conference,
Chief Data Officer event.
I'm Dave Vellante with my co-host, Paul Gillin.
Stewart Bond is here.
He's a Research Director
at International Data Corporation, IDC.
Stewart, welcome to theCUBE.
Thanks for coming on.
>> Thank you for having me.
>> You're very welcome.
So, your space, data intelligence.
Tell us about your swimline. >> Sure.
So, my role at IDC
is I follow the data integration
and data intelligence software market.
So, I follow all of the different vendors in this market.
I look at what kinds of solutions
they're bringing to market,
what kinds of problems they're solving,
both business and technical for their clients.
And so I can then, report on the trends
and market sizes and forecasts and such.
And within that, a part of what I cover
is everything from data integration,
which is more of the traditionally ETL change data capture,
data movement, data virtualization types of technologies.
As well as what we used to call data integrity
of what I'm now calling data intelligence,
which is all of the...
It's all the metadata about the data.
It's the data catalogs.
It's the metadata managements,
the data lineage.
It's the data quality, data profiling.
Master data intelligence.
It's all of the data about the data
and understanding,
really answering what I call answering
the five W's and H of the data.
It's the who, what, where, when, why and how of data.
So, that's the market that I'm covering and following.
And, It's why I'm here.
>> Were you here this morning for Mark Ramsey's...
Talk? >> Yes, I was.
>> So, he kind of went through, you heard it.
He started with EDW.
He kind of threw ETL under the bus
(chuckles) a little bit. >> Yes.
>> MDM, and then the Enterprise Data Model.
So, all of that failed.
But, that stuff's not going away.
I mean, I'm sure there are, you know,
Glaxo still using,
you know, all of that, too, in today.
So, what was your reaction to that?
Were you nodding you head then,
yeah it's true or saying,
well, maybe there's a little...
>> Well, haven't we been saying the mainframe's
going to go away--
>> Yeah. >> For years
and it's still around.
So, I think that obviously
there's still those technologies out there
and they're still being used.
You can look at any of the major ETL vendors
and there's new ones coming in the market.
So, that's still alive and well.
There's no doubt that it's out there
and it's the biggest segment in the market that I follow.
So, there's no-- >> There's open source tooling
right? >> Yeah.
There's no doubt that it's still there,
but Mark's vision of where things are going,
where things are heading with data intelligence
really being at the core.
He talked about those spiders.
>> Yeah. >> He talked about
that central repository of information
about knowledge of the data.
That's where things are heading
to whether you call it a data hub
or whether you call it a data platform.
Not really a one big huge data platform,
one big huge data repository
but one place where you can go to get the information
about the data.
So, you can find out where the data is.
So, you can find out what it means,
both the business context
as well as the technical information.
You can find out who's using that data.
You can find out when it's being used,
why it's being used
and why do we even have it
and how it should be used so it's being used appropriately.
>> So, you would say that his vision,
well actually what he implemented was visionary.
He's skating to the big...
They skated to puck so to speak.
Is that-- >> Yes.
Yep, yep.
And we're going to see more of that.
We are seeing more of that.
That's why we've seen such a jump in the number
of vendors that are providing data cataloging solutions.
I did...
IDC has this work product we call a Market Glance.
I did that beginning of 2018.
I just did again the middle of this year,
and the number of vendors that offer data catalog solutions
has significantly entries.
Like, 240% increase in the number of vendors
that offer that now.
So, if it's a small base,
these aren't all exhaustive studies
and maybe that I didn't know
about all those data catalog vendors a year and a half ago
or may also be that people are now seeing
well we've got a data catalog.
But, you've really got to peel back the layers a little bit
and understand what these different data catalogs are
and what they're doing,
'cause not all of them are created equal.
>> Well, it hit your radar.
If you don't know about it, you know,
99% of the world doesn't know about it.
So. (Steve laughs)
>> Mark talked this morning about some interesting
new technologies they were using.
Spidering to find the data. >> Yes.
Bots to classify the data,
tools to wrangle the data.
I mean, there's a lot of new technology
being applied to this area.
What...
Which of those technologies do you think
has the greatest promise right now
and how automated can this process become?
>> It's the spidering and it's the cataloging of the data.
It's understanding what you've got out there.
That is growing crazy.
We've just started to track that
and it's growing a lot.
That has the most promise.
And as I said, I think that's going to be
the data platform of the future,
is the intelligence.
Knowing about where your data is
so you can then go and get it.
It's not a matter of
all the data is one place anymore.
Data's everywhere.
Data's in hybrid cloud.
It's in on-premise.
It's in private clouds and hosted.
It's everywhere.
I just did a survey.
Got the results back in June 2019,
just a month ago and the data is all over the place.
And so, really having that knowledge,
having that intelligence about where your data is,
that has the most promise.
As far as the automation is concerned...
The next step there,
it's not just about collecting the information
about where your data is,
but it's actually applying the analytics,
the machine learning and the artificial intelligence
to that metadata collection that you've got
so that you can then start to create those bots,
to create those pipelines
and start to automate those tasks.
We're starting to see some vendors move in that area,
move in that direction and it's a lot of promise there.
>> You guys,
at least
when I remember
of IDC, this software.
We've had this pretty robust taxonomy.
I'm sure it's evolved over the years.
So, how do you sort of define your space?
I'm interested in how big is that space,
you know, in terms of market size.
Is it growing?
Where do you see it going?
>> Right.
So, my coverage of data integration and data intelligence
is fairly small.
It's a small little market at IDC.
I'm part of a larger team that looks at data management
and analytics and information management.
So, we've got people on our team
like Dan Vesset, who cover the analytics,
the advanced analytics,
Chandana Gopal, Carl Olofson.
He's been on theCUBE e-covers,
database-- >> Datatbase, yep.
>> Management technologies.
Those...
I apologize.
I don't have that number off the top of my head.
(laughing) >> Okay, yeah, yeah, no.
But I mean, your space--
>> My space--
>> That software market is so fragment
and what IDC has always done well,
is you put people on those fragments
and you go deep in there. >> Right, right.
>> And so, somehow you've been able to
like not make your eyes bleed when you do that
and it's
a challenging job, (laughing) but--
>> So the data integration--
>> But, you put it all together.
That's important so. >> The data integration market
is about six and half billion dollars.
>> Substantial size.
>> Yeah, yeah.
>> But again, a lot of vendors.
>> A lot of vendors. >> Growing number of vendors.
>> Yep. >> And the market's growing?
>> The market continues to grow
as the data is becoming more distributed,
more disbursed.
There's a need to continue to integrate that data.
There's also that growing need for that data intelligence.
It's not that just...
You know, we've had a lot of inquiries lately
about data being fed into machine learning
and artificial intelligence.
And people realizing, our data isn't clean.
We have to clean up our data,
'cause we're garbage in, garbage out
is probably more important now >> Yeah.
>> Than ever before.
'Cause you don't have someone
saying I don't think that data is right.
You've got machines that are looking at data instead.
The...
The technology that's out there
and the problem with data quality,
it's not a new problem.
It's the same problem we've had for years.
A lot of the technology is there to clean that data up,
and that's a part of what I...
And so, I look at the data quality vendors.
Experian is here.
Syncsort.
And then all of the other data quality capabilities
that you get from an Informatica,
or from Pentaho,
or from a click through Podium.
That all is there.
And so, that part is growing and there's a lot
of more interest in that data quality
and that data intelligence side, again,
so the right data can be used.
Good data can be used.
The trust in that data can be increased,
but used for the right reasons as well
and that's adding that context
and understanding that semantic,
having all of that metadata that goes around that data
so it can be used most effectively.
>> I mean it's one of those markets that
may be relatively small.
It's not a hundred billion.
>> Right. >> But, it enables
a lot of larger markets.
So, okay.
So, it's six and a half billion
and it's growing at...
Is it growing single digits?
Double digits?
>> It's growing...
It's hovering around the
double digits. >> It is?
Okay, so it's pushing 10%. >> So, it's around 10%.
Yeah. >> And then,
who are the big players?
Who's driving the shares?
Is there a dominant player or there are bunch of--
>> So, Informatica is number one in the market.
>> Yeah, okay.
>> Followed by IBM,
and SAP's right up there.
SAS is there.
Talend is making a good-- >> Talend, okay.
>> Yep, they're making a nice headway in--
>> With a SAS approach, right?
>> In the size of, yeah.
But, there's a number of different players.
There's a lot of different players in that market.
>> And the leading market share player
has what, 10%, 15%, 50%?
Is it like a dominant share?
I don't want to put you on the spot.
That's tough to say. (laughing)
You've got to pull
a report against it. >> Informatica's big.
It's over a billion. >> Yep.
Right. >> It's over a billion, yeah.
>> So, they've got maybe a 1/6 of the market.
Okay, but it's not like Cisco.
Has 2/3 of the networking market
or anything like that. >> No.
>> And what about the cloud guys?
Are they participating in this?
How do you guys
deal with that? >> So, the cloud guys--
Yeah, the cloud guys.
So, there are some pure cloud solutions.
There's Reltio, for example.
PureCloud, MDM, Master Data Management.
There's...
I'd say there's less PureCloud than there used to be.
But, you know,
someone like an Informatica is really pushing
that cloud's presence and that cloud capabilities.
>> So, running this tooling in the cloud,
but the cloud guys, directly, are not competing
at this point yet?
Is Amazon-- So, Amazon, Google, yes.
So, those cloud guys?
Yes >> Yeah, okay.
>> They are...
Google announced Data Flow back in,
or sorry, Data Fusion back at
Google Cloud Next. >> Yeah, that's right.
Yep. >> And so, they've got
an ETL tool in the cloud now.
Amazon has Glue-- >> Yeah, right.
>> Which is both a catalog and an ETL tool.
Microsoft, of course, has data factory and Azure.
>> So, those guys are coming on.
>> They're coming on. >> I'm guessing,
if you talk to Informatica,
they said, well they're not as robust as we are
and we've got a big install base
and we go multi-cloud.
Is that kind of the posturing of the incompence or?
>> Yeah, that's the posturing.
Yes.
Maybe that's...
I don't mean it as a pejorative.
>> Right. >> If I were those guys,
I'd be doing the same thing.
But, we were talking earlier about
how the cloud guys essentially killed the dupe.
>> Right.
Do you see the same thing happening here or is it...
Will the tool vendors be able to stay ahead in your view?
>> It depends on how they execute.
And if they're there and available on the cloud
along with those cloud providers
and they're able to provide solutions
in the same way, the same elasticity,
the same type of consumption based pricing models
that the cloud vendors are offering;
if they can compete with that,
they still have better solutions that what--
>> And mutli-cloud and hybrid is a big part of their
value problems >> It is.
>> that the cloud guys aren't really going hard after.
>> I mean, they're sort of dangling their toe in the water.
Some of them there, anyway.
>> And some of the cloud guys,
they have the hybrid capabilities.
>> Right.
'Cause they've got some of what they've built
comes from on-premises worlds as well.
So, they've got that ability to--
>> Microsoft in particular,
right yeah? >> Microsoft and Google.
Google, >> Yeah, with Anthos.
>> The day fusion came out of the...
>> You're saying as part of the Anthos initiative, or?
>> I apologize, if the Google folks are watching,
but I've (chuckles) >> Yeah, I know.
(crosstalk) >> I've forgotten
the name of that. >> It's a soup of acronyms
in our business. >> It is.
>> Change the subject a little bit, the--
>> What tools have you seen
or technology have you seen
for governance of unstructured data that looks promising?
>> So, I don't really cover the unstructured data space
that much.
What I can say is
just as in the structured data world,
it's about the metadata.
It's about having the proper tags
about that unstructured data.
It's about getting the information
about that unstructured data so that it can then
be governed appropriately.
It's making structure out of that, that is...
I can't really say because I don't cover that market
explicitly, but I think, again.
It comes back to the same type of data intelligence.
It's having that intelligence about that data,
about understanding what's in there.
>> What advice are you giving to the buyers
in your community and the sellers in your community?
>> So, the buyers within the market talk a lot about
the need for that data intelligence.
So, data governance, to me, is not a technology.
You can't go out and buy data governance.
Data governance is an organizational discipline.
Technology is a part of that,
and to me, the data technology is a part of that.
So really, organizations, if they really want a good handle,
get a good handle on what data they have,
how to use that data,
how to be enabled by that data,
they need to have that data intelligence.
They need to go out and look for solutions
that can help them pull that data intelligence up.
But the other part of that is measurement.
It's critical to measure,
'cause you can't improve when you're not measuring.
So, that type of approach, too, is critical.
And you've got to be able to have people
in the organization.
You've got to be able to have cooperation,
collaboration across the business.
The IT, the Chief Data Officer office.
You've got to have that collaboration.
You've got to have accountability
in order for that to really be successful.
For the vendors in this space,
hybrid is the new reality.
In my surveyed data,
it shows clearly that hybrid is where things are.
It's not just cloud.
It's not just on-premise.
It's hybrid.
That's where the future is.
They've got to be able to have solutions
that can work in that environment,
that can work in that hybrid cloud ability.
They've got to be able to have solutions
that can be purchased and used again
in the same sort of elastic type of method
that they're able to get,
that consumers are able to get services from other vendors
in that same type of-- >> Great.
All right, Stewart.
We've got to run. >> Okay.
>> Thank you so much for sharing your insights
and your data.
I know we were firing,
I was firing all the questions at you.
You did pretty well (chuckling)
with not having a report in front of you.
I know what that's like.
So, thank you for sharing
and good luck with your challenges in the future.
You got...
You got a lot of data to collect
and a lot of fast moving markets.
So, come back anytime and share with us
your update. >> A good space to be
right now. (laughing)
>> Okay, and thank you for watching.
Paul and I will be back with our next guest
right after this short break from MIT CDOIQ.
Be right back.
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