At a glance, the data governance process might seem like a never-changing corner of the data management world. A data governance policy and associated procedures need to be created and implemented to help keep corporate data consistent and ensure that it meets the information needs of business users -- that's it, right? If only things were so static. But technology is always evolving, and disciplines like data governance and data stewardship need to evolve along with it.
In a report released in July 2013, consultancy Forrester Research Inc. pointed to self-service business intelligence, big data, cloud computing and other tech trends, and said data governance needs to become "more agile and operational" -- not just a committee-driven process with rigid rules set by a data governance council and enforced by data stewards. "Command-and-control data governance creates a culture of 'no' that stifles innovation," Forrester analyst Michele Goetz wrote in a blog post that same month. She recommended the adoption of "data governance zones," with different levels of standards for different applications and data sets.
And then there's the question of how much involvement IT departments should have in data governance and stewardship efforts. In many cases, IT is taking the lead -- but governance "is not a separate discipline that operates outside and independent of business operations," Gartner Inc. analyst Andrew White blogged in August 2013. Without business leadership, White warned, companies will have a hard time making a data governance strategy stick.
You'll find a variety of content on SearchDataManagement aimed at helping you ensure that your organization is well-versed in data governance best practices. In one article, consultant David Loshin offers tips on setting up and managing teams of data stewards. In another, he gives his take on the role of automated data governance software. We also look at the intersection of big data and data stewardship as part of a data governance policy, and we interview Sterling National Bank executive Patrick DeKenipp on using the Data Management Maturity Model to help improve governance programs and other data management processes. In addition, we've compiled more articles, relevant definitions and a short quiz in a guide to building data governance frameworks. Good luck keeping on top of your ever-changing governance efforts -- hopefully we can be of some assistance with that.
This was first published in January 2014