Big Data is a big issue in IT, but is it time to invest in the tools and infrastructure to deal with big data as a unique enterprise asset? It's a question many CIOs are wrestling with, and one that we attacked in the latest E2 Great Debate: Invest Big in Big Data.
The debate, between Tony Hamilton, enterprise marketing manager for Intel Data Center and Connected Systems Group, and Thomas Redman, founder of Navesink Consulting, was lively, enthusiastic, and informed by decades of enterprise IT experience. The chat that began before the debate and continued through and beyond the debate itself was free-wheeling and passionate on many aspects of the topic. In the end, the result was a community with far more knowledge and perspective on big data than had been the case an hour before.
Before we get to revealing winners and losers (OK, to be honest there are no losers in a debate like this: everyone learns a lot and we all walk away as friendly colleagues), let's look at some of the things we learned.
Tony came to the debate from the "pro" position, arguing that the time is right to begin investing in big data as a unique enterprise asset. Thomas took the "con" position, arguing that, while big data may be an important enterprise asset, companies should be investing in data handling and analysis basics before leaping on to the big-data-specific bandwagon. In many aspects the two agreed with one another, neither arguing that big data isn't important or that companies need to establish, learn, and follow established business intelligence procedures. On a couple of areas, though, there was a significant difference of opinion.
Thomas argued that the benefits of investing money specifically for big data don't outweight the benefits of spending the same money on "data basics," building a successful data analysis and business intelligence function that works across all aspects and types of data held by the enterprise.
Tony's position was, in some ways, more optimistic, assuming that the basics in the enterprise have been sufficiently covered to allow highly profitable investment in a new entity called "Big Data." The differences were important, yet carefully nuanced, and E2 Platinum Member Rowan summed up the debate with:
While this was framed as a pro/con debate, I more got the feeling that it was really a more similar discussion about being careful or not. The answer that seemed to be synthesized was that if your company is being careful, expanding data operations, but if you had room to make that expansion, it's probably a good thing.
What did the community learn? E2 editor in chief Sara Peters found three key lessons:
So, let me synthesize what I've learned today -- Tom and Tony let me know if you disagree. It sounds like the first place to start with any big data project is to #1 Talk to your business leaders about what INSIGHTS they want to actually squeeze out of all this data, #2 Make a strategy to deliver those insights, #3 Establish the right processes and purchase the right tools to make sure that you're collecting VALUABLE data and keeping it SECURE... how am I doin'?
The consensus of the community was that she had done just fine.
After all the talk and chat, who won? The E2 community said that the "pro" side was the more compelling argument. The margin was decisive, 70 percent to 30 percent, a ratio that remained consistent throughout most of the voting cycle. In truth, this was an acknowledgment that big data is here to stay, and that companies must begin investing today if they're not going to lose a competitive advantage. It's the optimistic move to make.