Today VMware made an acquisition that's extremely interesting from several perspectives: cloud, virtualization stacks, big data analytics and more.
Cetas describes themselves as ".. an early stage startup that delivers Analytics-as-a-Service to customers and is driving the democratization of analytics and business intelligence by dramatically lowering the barriers to entry for all companies, from SMB to large enterprises."
Yes, quite true when they were a standalone entity.
But as part of the VMware (and, by extension, the EMC) family, it gets much more intriguing indeed ...
Big Themes In Play
One of the defining attributes of any form of virtualization is that it makes things easier to consume -- and easier to produce.
Virtualize your storage farm, and the same thing happens.
Virtualize your databases with something like vFabric Data Director, and you'll see it once again.
The "vending machine" analogy works well here.
In one sense, Cetas virtualizes big data analytics. They help make predictive analytics easier to consume and easier to produce.
So you might ask -- why is that important?
Making Something Easier To Consume Means More Of It Will Be Consumed
As part of my day-to-day customer engagements, I will routinely delve into the amazing potential of predictive analytics powered by big data.
Thanks to a veritable torrent of new information sources, dropping resource costs and powerful new algorithms, today's data science practitioners can do mind-bending things if given the right tools.
Three out of four people listen to me go through my talk track, and nod politely at the end. But -- once in a while -- someone in the audience gets all fired up, and says "wow -- we gotta get going on that -- how do we start?"
I then take out our three-phase model that describes how many organizations achieve analytical proficiency.
The first stage in the typical journey is to make your existing data incredibly easy to consume. For many, this takes the form of an "analytics as a service" capability, or sometimes "BI as a service". We've got just such an initiative going on in our own EMC IT world, and many of our customes are now working in the same direction.
Move past the traditional role of IT being the High Priests Of Authorized Data Access.
And, if you can get good at that, you've created an environment where data science professionals can more easily work their unique magic, and you're off to the races.
It's a small world -- two of the principles at Cetas (Muddu Sudhakar and Karthik Kannan) I once knew as part of the Kazeon acquisition. Well, they're back again!
Cetas currently targets three popular analytics use cases.
The second is the growing area of IT operational analytics: advanced IT professionals who are starting to use analytical tools to measure and better understand their own operations -- think Splunk.
And, finally, the emerging area of enterprise big data analytics, build around Hadoop and other tools.
Because they're built on VMware technologies, Cetas can easily support all three cloud consumption models: private, public and hybrid. All at once, analytics gets a whole lot easier to consume and produce.
And, as you'll hear me often say -- things which are easier to consume tend to get consumed more.
The VMware Tie-In
For starters, VMware is working on building out their overall data strategy (think vFabric Data Director) as well as their Cloud Application Platform (think Cloud Foundry and related PaaS assets).
A clear and obvious fit there.
Additionally, VMware is investing heavily in its management stack (vCenter Operations and related) which will obviously benefit from a strong analytics component.
As we move from physical to virtual to cloud, predictive analytics is turning out to be an essential weapon in the IT management arsenal.
Finally, VMware now has an obvious tie-in at the "consumption layer" of the newer, Hadoop-based big data analytical stacks.
The Greenplum Tie-In
As the part of EMC that's spearheading our initiatives into big data analytics, Greenplum wins big as well.
Greenplum has strengths at the database layer (the ubiquitous Greenplum Database), an enterprise Hadoop distribution (Greenplum HD), a purpose-built data science collaboration environment (Greenplum Chorus) as well as a healthy roster of card-carrying data science professionals available through the Greenplum Analytics Lab.
Although if you drew Greenplum's "stack", you'd see they might be in need of a few key components: a database provisioning layer as well as a virtual machine orchestration and management layer built for the workloads at hand.
Both now can potentially and ideally be sourced from the growing VMware data layer.
The EMC Tie-In
Look at our corporate messaging, and you'll see three big themes: cloud, big data and trust. Cloud is changing IT. Big data is changing the world. And trust allows us to do both with confidence.
Cetas fits nicely into this schema: advancing and extended existing themes. A very smart acquisition from where I sit -- especially when you consider the context of both VMware and the broader EMC.
More importantly, Cetas adds important differentiation to these themes.
Clouds are moving from generic to more purpose-built, and predictive analytics is quickly shaping up to be one of the more compelling use cases for specialized clouds. The big data analytics world is getting crowded fast, Cetas helps us differentiate by improving the consumption and production model around predictive analytics. For a related view, check out GigaOm's take.
There's more to the story, but that's enough for now.
I'd like to extend my personal congratulations to both the VMware and Cetas teams -- exciting times ahead!