Shadow Analytics: Quicker Results, but Often at the of Cost Creating Non-Secure Siloed Data

first_imgShadow IT refers to the use of apps and external IT services without consulting internal IT resources.  It’s an end-run approach that many departments are increasingly using when they feel that traditional IT “help” just gets in their way.  Increasingly, departments are using Shadow Analytics and Shadow Business Intelligence.It was found that more than 40 percent of organizations are bypassing their local IT group and using Shadow Analytics.  Another report found that 59 percent of the respondents said that the use of Shadow Analytics often leads to data governance problems.Francois Ajenstat, chief product officer at Tableau, said that “the people who want to use data will use any piece of software to get what they need. It starts with a frustrated individual who knows that analytics can help her do a better job.”Bob Familiar, practice director at BlueMetal, said that “what’s driving shadow analytics is the desire for data in real time and near real time — marketing, lines of business, product owners, and manufacturing environments. It can show up almost anywhere if IT has not provided those capabilities, an X-as-a-service, on-demand, self-service experience.”One major problem is that the use of Shadow Analytics often requires data to be moved to non-secure public repositories. But another problem is that when data usage isn’t centralized, it isn’t possible to see the complete picture.  Stephen Baker, CEO of Attivio, said that “enterprises are competing on an incomplete view of their data; they cannot adequately see or unify data across their silos. The need for immediate visibility into the right information continues to be the last mile in establishing these organizations as true data-driven companies.”last_img