So, what's going on here -- and why are many of us so excited?
Yes, there are cool new capabilities from Greenplum that help accelerate the impact of data science, and yes there's a very cool group of agile app developers and tools from Pivotal Labs.
But how do these themes tie together, and how to they complement other pieces of the puzzle that we're assembling on the behalf of our customers?
To Begin With
One of the images that I use frequently is this stark comparison of business models.
Newer digital business models appear to be fundamentally different: information in, insight out -- all built around a digital business platform that powers your value proposition.
If you happen to be fortunate enough to work for a company that was "born digital" (or has essentially become that way), you fundamentally understand the latter model, and have little appreciation for the former one.
The IT discussions are typically extremely business focused as a result.
However, if you're not so fortunate, you have two styles of IT to master.
First, there's the traditional style of IT that's all about automating business processes and delivering IT services that support today's business. Plenty of that around to keep everyone busy.
But more recently, it appears that there is a newer task at hand: the challenge of building the digital business platform that will power tomorrow's business model. Put differently, creating IT for strategic business advantage.
IT leadership is often put in the precarious position of having to serve these two divergent masters, both with apparently conflicting needs.
It's this newer IT mission -- one focused on value creation and digital business models vs. legacy process optimization -- that EMC is investing so heavily in these days.
We're Learning A Lot About This New World
Welcome to the world of the "new stuff": mobile consumers and knowledge workers, social engagement, big data, predictive analytics, "fast data" business processes -- all wrapped in agile application development, and built on agile cloud services.
If you live in this world, you know what you need. If you're starting to move in this direction, you have a strong incentive to start to minimize the old ways of doing things, and start to invest in getting more comfortable in the new way of doing things.
Individually, each of these topics is worthy of a discussion in itself; collectively they represent the new face of IT and extracting value from information.
New ways of doing business with information means new tools, and that's the primary rationale behind today's announcements.
Part I -- Greenplum's Chorus Announcements
When EMC acquired Greenplum back in 2010, they were mostly focused on building a better "big data" database to power the newer flavor of analytics applications.
Since then, the mission has quickly evolved toward creating the newer tools and environments needed to practice data science.
Data science is usually conducted as a team sport, and teams generally prefer to collaborate using the familiar social paradigms. That's the rationale behind Greenplum's new social collaboration capabilities aimed squarely at data science teams and those that work with them.
Additionally, Greenplum announced their intent to open source their Chorus collaboration environment.
What I found interesting was the key motivation: open sourcing as a mechanism to stimulate and accelerate innovation.
Data science is quickly becoming very important to so many organizations, and the whole concept of social collaboration amongst data science professionals (who may not even work for the same organization) is a relatively hot topic. As a result, innovations are occurring at a breathtaking pace.
By "opening up" Chorus, the goal is simple: harness the power of open source models to accelerate the productization of these innovations.
Part II -- Greenplum Acquires Pivotal Labs
At first blush, Pivotal Labs is extremely cool in their own right. From my perspective, their sweet spot is creating thoroughly modern applications using thoroughly modern tools and methodologies. But how do they fit in with big data analytics?
If I refer back to the model we've been using around how organizations achieve big data analytics proficiency, there appear to be three clear phases.
The first phase is an investment in learning how to expose and consume existing internal data sources more effectively. Call it "BI as a service", the goal is encourage consumption and experimentation with existing data sources.
For example, one of the cooler projects EMC IT is working on is our own internal BI as a service capability, and it's producing not only the expected results, but a few amazing surprises as well.
The second phase is to bring in the data science team, and let them work their unique magic. Before long, they'll typically start to find amazing predictive insights in the data. But what do you with those insights?
The third phase is to quickly operationalize those insights into new processes and new applications. To do this, you'll need a thoroughly modern "application factory" with modern tools and modern methodologies. That's just one of the ways that Pivotal Labs fits in to our bigger picture.
Based on what I've seen, once the basic "information supply chain" is set up -- from raw information to analytical insight to operational changes -- it quickly becomes all about speed.
How fast you can provision a new data set and make it easy to consume by anyone.
How fast the data science team can discover new and meaningful insights.
And how fast you can translate those insights into running applications that act those insights.
To be fair, the vast majority of traditional IT organizations I meet with look at all of this with a wistful eye.
Privately, they want to start doing this sort of thing, but so many obstacles appear to lie in the way: budget, resources, governance, skills, etc. A precious few have decided to break off a small team, and start to do things very differently when it comes to creating value from information. And, generally speaking, they're starting to get amazing results, which means there's more resources and enthusiasm, and progress accelerates.
Where the real hunger lies is in a handful of business leaders I've met. They realize something extremely important is afoot, and are trying to figure out (a) what it could mean to them, and (b) how to get started. They're willing to invest to get started.
And -- in a small handful of instances -- the IT team and the business team have linked arms around creating an entirely new set of information capabilities for the organization. It's not so much around optimzing the old model, but learning to thrive in the new one.
When you see it, it's a wonderful thing.
And I can only hope we see more before long.