These are curious times. The media is drilling big-data hype into everyone’s skulls, but how many businesses making a go at it are striking gold? One Gartner analyst estimates a shockingly high failure rate for big-data projects at 85 percent (paywall report here). Perhaps that’s because few vendors and experts have the grit to formulate the right products and practices.

IBM Corp. has volunteered itself as a guinea pig in the messy, poorly-lit lab that is big-data analytics. For the last few years, Big Blue has been feeling its way through to cognitive business. It has kept tabs on failures and successes in tools, technologies, and working methods, and is bottling up the knowledge and selling it to customers.

“What we can do is pull together the right breadth and depth of IBM resources, deploy it and customize it to customer needs and really hopefully accelerate and apply a lot of what we’ve learned, a lot of what our clients have learned to accelerate their own artificial intelligence transformation journey,” said Caitlin Halferty (pictured, left), client engagement executive, global chief data office at IBM.

Halferty and Sonia Mezzetta (pictured, right), technical product leader, data governance at IBM, spoke with spoke with Rebecca Knight (@knightrm) and Paul Gillin (@pgillin), co-hosts of theCUBE, SiliconANGLE Media’s mobile livestreaming studio, during the IBM CDO Summit in Boston, Massachusetts. They discussed IBM’s artificial-intelligence initiatives and the evolving role of chief data officer. (* Disclosure below.)

AI for metadata for AI

Metadata, or the data about a company’s data, is the best way forward for those unsure where to start with big-data monetization, Mezzetta said. “In order for you to have the right data governance, you need to have the right metadata,” she said.

IBM showcased its automated metadata generation tool at the summit. It leverages automation and AI to slice through some dense metadata-curation blocks. It shortens the often tedious, manual process of data labeling, she said. This helps data officers begin a project with clean, labelled data from the get-go.

Don’t get too excited — no technology can do it all. AI for business is complicated and needs trained humans in the loop, Halferty said.

The scope of the CDO is broadening and moving to the level of the chief information officer. There, the CDO can execute decisions about technology investments, etc.

“We tend to find that when [the CDO] is potentially buried in the CIO’s organization, you lose a little of that autonomy in terms of decision making,” she said. “So if you’re able to position as partners and drive that transformation for your organization forward together, that can often work quite well.”

Watch the complete video interview below, and be sure to check out more of SiliconANGLE’s and theCUBE’s coverage of the IBM CDO Summit. (* Disclosure: TheCUBE is a paid media partner for the IBM CDO Summit. Neither IBM, the event sponsor, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE