Weaving Data Fabrics

Only recently, I caught up to the Spike Jonze movie "Her" from last year. I was struck by the way the film placed advanced technology into a world very similar to what many people now encounter on a daily basis. If you aren't already way ahead of me on this movie, "Her" centers around Joaquin Phoenix falling in love with the operating system on his smartphone (an advanced fictional version of the Apple iPhone Siri personal assistant, voiced in the movie by Scarlett Johansson).

The pivotal turn of the movie [big SPOILER here] is when poor Phoenix is told that the object of his affections, the "OS" (operating system) has been "dating" thousands of other guys at the same time and also fallen in love with several hundred of them, all at once. Johansson's virtual character has computational power similar to what was demonstrated a few years ago by IBM's Watson on "Jeopardy." In the way Watson could access answers with inhuman speed, the "OS" in "Her" could carry on simultaneous conversations and affairs with many people, also learning about personal relationships and growing personally at the same time. Not that this was much consolation for Joaquin's character.

This fictional instance suggests the existence of a chaotic data world—either that Johansson's "OS" character exists in or actually creates. It's not that far off from a real chaotic data world, and overwhelming stores of big data in the real world, and the financial industry, which is something the president of Teradata Labs, Scott Gnau, spoke about at the company's Teradata Partners conference in Nashville, Tenn., last week.

"In our businesses, we're trying to combine all kinds of data technologies to harness the uncontrollable data chaos all around us," he said. "We integrate it all into something that produces real value and real meaning. Each of us is trying to do this exact same thing every single day in our own organization."

Separate from this remark in a general session opening the conference, Gnau drilled down into what big data chaos means for financial services firms trying to deal with it. He advocated addressing the data fabric within a firm—the totality of the data being collected and the tools that are being woven together to collect it. Replacing or correcting all the data is more expensive and cumbersome than the tools being used, Gnau said. By focusing on the data layer of the data fabric, improvements to the entire fabric, and thus the overall data operations of the firm, will come more easily, he added.

After all, in the real world, the industry does not quite yet possess the type of artificial intelligence that can manage multiple relationships, generate its own insights and act on those insights. So Gnau's point that the data fabric matters more than the tools—the operating systems—makes sense.