Judith Hurwitz, Hurwitz and Associates, at IBM Information on Demand 2013 with John Furrier and Dave Vellante @thecube #IBMIOD Judith Hurwitz, the president and CEO of market research firm Hurwitz and Associates, stopped by SiliconANGLE’s theCUBE at the recent IBM Information on Demand 2013 summit in Las Vegas to share her perspective on Big Blue’s analytics strategy. IBM is expanding in all directions, with hardware and software solutions for ingesting, processing and visualizing Big Data. Together with predictive analytics, these capabilities converge in the company’s cognitive computing offering, which Hurwitz calls the “next stage beyond the data.” The way she sees it, the technology marries automation with machine learning to provide greater visibility into metrics, correlations and other important factors in driving meaningful insights. Cognitive computing addresses many of the challenges faced by traditional IT shops that are only starting to tap into their vast troves of information. These companies implement their Big Data deployments as isolated projected or in individual business units, creating silos which Hurwitz says will only become more numerous as the adoption of analytics accelerates. Changing topics, she highlights that the diversity of data sources and analytical methods makes it harder than ever – if not impossible – for organizations to reach a single version of the truth. It all boils down to information quality, she explains. “Big Data sources are by their nature dirty. If it’s social media, some of the results could be that company planting a lot of information about ‘isn’t this service great and we’re so happy,’” Hurwitz says. “So yes you wanna grab as much data as possible, but that’s why we talk about going from big to small. It’s the small data that’s really important, the Big Data is just your starting point.” To uncover insights, companies must not only identify patterns and anomalies in their data but also accurately determine the relevance of the results. Security and governance are also top priorities, especially when it comes to handling fast-moving workloads that may contain sensitive information. Watch the clip below for the full highlights from the interview, including more on the state of analytics, the Big Data knowledge gap, and the ambiguous role of the chief data officer.