At a recent federal government summit all attention was on big data. Interestingly, the need for "more governance" was raised by a speaker -- and seconded by another -- as a critical enabler for innovation in the big data era. Panelists discussing potential opportunities and pitfalls of text and social media analytics agreed.
Why? Organizations undertaking the "big data" journey are confronted by a myriad of decisions and issues. They are running headlong into policy, privacy, and risk-based questions regarding the appropriate use and sharing of such data, particularly in the case of social media and other "public" sources in which the data creator may not even be aware that an organization is accessing their information. Even fewer enterprises understand how big data is being used.
Complicating matters, what constitutes "appropriate use" is different for each organization. Considerations include applicable regulatory/compliance mandates and each company's risk tolerance and stated policy. Add to the mix the need to prioritize opportunities and make changes to existing business and data practices to leverage the data itself, and the complexity is apparent.
Of course, conversations about governance often invite the specter of bureaucracy and raise fears regarding protracted decision-making processes and loss of agility. In fact, the opposite is true. Good governance mandates rapid decision making and streamlines business and IT processes. It also helps manage risk proactively.
Sans governance, judgments about "appropriate data use," for example, are made by individuals on a case-by-case basis. That judgment may or may not align with the organization's risk tolerance or how it sees itself. No two people may wield the data in the same way. Alternatively, projects or decisions get hung up while business and IT groups wrangle. Without defined guidelines, policies, and processes for resolving such issues the process often stalls -- sometimes indefinitely, or the decision is made, by default, by those who speak the loudest or the longest. Finally, in the absence of a pragmatic and flexible mechanism for vetting and balancing risks, legal and regulatory concerns can stop even the best laid plans in their tracks. ROI or not, "no" is almost always easier and perceived to be less risky than "yes."
The bottom line is that ad hoc decision making -- particularly when it comes to data (big or small) -- can be capricious at best. When designed well and leveraged to support business initiatives, data governance clarifies decision making and provides clear rules of the road for data acquisition, usage and sharing. This clarity and rigor drive agility and lower risk. In today's fast-paced world, this can be the difference between being competitive and falling behind.
Kimberly Nevala is a director on the SAS best practices team. She specializes in strategies for BI and analytics, data governance, and information management programs and conducts client workshops and industry presentations in these areas. You can contact the author at email@example.com.
©2013 by TDWI (The Data Warehousing Institute), a division of 1105 Media, Inc. Reprinted with permission. Visit tdwi.org for more information.