A month ago we held a webinar entitled “Disentangling Discovery and BI— Understanding the Differences between Birst and Tableau.” The webinar detailed a new study conducted by Blue Hill Research. The study examined results from firms that were interviewed after they evaluated data discovery tools and BI platform solutions and ultimately, chose a BI platform. The webinar focused on why five large organizations made this choice and looked at the rationale behind it.
Something clearly resonated. The webinar set registration and attendance records at Birst and continues to be our top on-demand webinar in Birst’s online Resource Center. We also continue to receive inquiries from organizations evaluating BI who make reference to the research.
Why all the interest and what chord was struck with so many? I believe it comes down to something that is gaining increased attention and has been a topic of discussion amongst the analytic digerati. Gartner calls it “governed data discovery” in their recent Magic Quadrant for Business Intelligence and Analytics and describes it as “platforms that address both business users’ requirements for ease of use and enterprises’ IT-driven requirements.” The report explains how many organizations find data discovery tools attractive, but lack the necessary enterprise features in relation to governance, administration and scalability—clearly things that are critical for IT and important when looking to deploy an application throughout an organization.
In Blue Hill’s research note, Anatomy of a Decision: Birst vs. Tableau, analyst James Haight interviewed five organizations spanning across the largest healthcare providers in the US to one of the world’s largest engineering software providers who had selected Birst over Tableau for their analytic needs. In his interviews he came across a few common themes which echoed across all his participants. These included the emphasis on broader user access and adoption, the need to scale with expanding data sources as well as the need to connect to multiple data sources and the need to present a unified approach across each level of data analytics. It was especially this latter point that was highlighted as the most important requirement and Haight noted “for insight to be gleaned from data it must be managed throughout the process of collection to analysis.” Blue Hill went on to state that the fundamental theme to arise from the study was a discussion of the merits of a BI platform as compared to a BI ‘tool’.
It’s this distinction and understanding the real differences between a BI platform and a data discovery tool that, I believe, lies at the heart of what governed data discovery is all about. Data discovery is still a relatively recent entrant into our lexicon and analytics strategy and many organizations need help in understanding just how it fits into the more holistic umbrella of business intelligence. Data Discovery is not a silver bullet that will solve all of the issues with legacy BI. I believe our recent webinar and this research are getting the attention that they are because they are helping to more clearly delineate what organizations need when employing analytics and better understand the concept of what governed data discovery is all about.