Wayne Eckerson points out in a recent report that, "Business intelligence (Bl) is fueled by two opposing forces: top-down BI, in which the corporate IT group imposes standards on the delivery of data and reports to ensure a single version of truth, and bottom-up BI, in which business unit analysts create their own reports with custom data sets." Or more simply, it's the data warehouse folks versus the fans of Hadoop and the
The Chief Data Officer has never been a more necessary role in the organization than it is today. Organizations capture and store more data than ever before, and it’s growing exponentially every year.
Not only is business data growing, but we are seeing new types of data continually entering the mix. Data is structured, unstructured and semi-structured. It’s stored in big data lakes, in business applications, in file shares, and other places across the organization. There’s so much data that even the CDO isn’t completely aware of what’s out there.
Every organization recognizes the value of agility — the ability to work with our data iteratively and flexibly, pulling data from any source as needed for insight. To achieve agility, we work and rework the data stack, adjusting and rebuilding and tweaking everything from the data lake to the visualization tools. Too often, though, we fail to achieve agility in terms of the flow of data in the organization.
As we’ve pointed out in two previous white papers, data discovery is a three-part process. Profile and identify—the first two steps—reveal where data resides and what it contains. The third step—unify—is the final step to full data self-service. It provides business analysts and data scientists with the connections and relationships between data elements that unleash the power of data.