TheCube hosts Dave Vellante and Jeff Kelly wrapped up the first day of this week’s MIT Information Quality conference with an in-depth discussion about data quality and the evolving role of the CDO.

Dave points out that information security and data quality, two of the newest trends in the Big Data space, are among the main themes of the event. He adds that organizations across all verticals are looking to integrate their isolated data silos in an effort to address business problems, but it’s much easier said than done. Jeff agrees about data quality being a major highlight at MITIQ, and notes that the chief data officer is also at the center of attention. CDOs have the responsibility of identifying and resolving business problems by applying analytics to their organization’s’ data assets.

Dave gets back to data quality, and stresses that enterprises can’t gain a holistic view of their customers without a single version of the truth. Obtaining it requires consolidated and cohesive data infrastructure, a vision that the industry is still trying to realize.

“What I see happening is a lot of heavy lifting. Practitioners are trying to start understanding this problem, they’re getting to the root cause, they’re putting together data architectures,” Dave tells Jeff. “They’re dealing with this Big Data as an opportunity, potentially to use analytics to resolve some of the data inconsistencies but also as a way to drive business value in a way they perhaps couldn’t with traditional methods.”

Big Data professionals face increased pressure to meet end-user expectations, namely the demand for quick and convenient means to access information. Because the task of managing data doesn’t overlap with traditional IT roles, Jeff believes that more and more organizations will appoint CDOs to help them monetize their data.

Jeff considers information quality to be a requirement for effective analytics strategies, but Dave says that it varies across industries. He explains that a healthcare provider can’t afford to mix up patient records, but companies like Google have successfully generated value using less than accurate data.

See the video below for the full discussion.