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BI self-service tools need middle ground on use, governance

Deployments of self-service BI and data discovery tools need to be governed to keep things in order. But finding the right balance between user freedom and IT oversight isn't always easy.

In its 2015 Magic Quadrant report on business intelligence and analytics platforms, consultancy Gartner pointed to a "fundamental" change taking place in the BI market: an accelerating move from large-scale, centralized systems to self-service BI applications that put data discovery and interactive analysis capabilities in the hands of business users. Gartner said more than half of the revenue from new purchases is now being driven by deployments of BI self-service and data discovery software, which lets users steer their own course on running analytical queries and building BI dashboards.

The potential downside of self-service BI is that decentralized analytics processes can get out of control, resulting in inconsistent data and bad business decisions. Gartner predicted the percentage of self-service projects governed effectively by IT and BI teams will only be in the single digits through the end of 2016.

BI vendors increasingly are taking note and touting the data governance capabilities in their products. But IT and BI managers pushing the governance issue risk being viewed by business users as "the police," as one speaker put it at the 2015 TDWI Executive Summit in Las Vegas. The trick, Forrester Research analyst Boris Evelson said in an interview last year, is finding some middle ground "where you can empower business users to be self-sufficient, but monitor what's going on."

SearchBusinessAnalytics and SearchDataManagement editors have posted a variety of content offering insight and advice on locating that middle ground and managing successful self-service BI and data discovery initiatives. In a story from the 2015 BI Leadership Summit in New York, we look more closely at the challenges of striking the right balance in governing BI self-service processes -- and big data environments -- with comments from Evelson, other conference speakers and attendees on how to make it work. Another story details the collaborative approach to BI governance taken by pension fund manager CDPQ. In a third article, consultant David A. Teich offers his take on the continuing role of IT and BI teams in supporting -- and overseeing -- users of self-service and data discovery software.

In addition, we explore data discovery projects at two organizations and the importance of building a solid data architecture to underpin self-service BI efforts. We also document strategies for increasing the adoption of BI self-service software in organizations, including examples of how BI managers at two companies succeeded at integrating self-service tools into operational workflows. And we take a more in-depth look at the BI and analytics trends highlighted in the 2015 Gartner Magic Quadrant report on BI platforms.

Next Steps

Consultant Wayne Eckerson on the complexities of managing self-service BI projects

Charitable groups turn to BI self-service tools to try to boost fundraising and operations

Check out our guide to implementing self-service BI and data discovery software

This was last published in January 2016

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