Big Data Initiatives: Minimizing Risk and Maximizing Value with Governance

Abstract

Big Data Analytics can be a fantastic business opportunity for many organizations. Already organizations are using advanced analytics to streamline production processes, optimize back office activities, market more effectively, and better satisfy customer demand. That said, it goes without saying (as recent headlines can attest) that sometimes enhanced analytics capabilities can introduce risks such as erosion of privacy, overly-intrusive knowledge about customers, etc.

Given this dichotomy, making the decision about when, whether, how much, and how to invest in big data analytics initiatives can be a challenge. Invest too soon and you may obviate existing investments or disrupt business activities; invest too late and you may find that competitors gain advantages that make the market landscape asymmetric.

This article outlines how and why applying “tried and true” governance principles can help make this decision easier. For those that have formalized governance structures in place, how they might inform the decision an organization makes in this regard – and for those that don’t have a formalized governance program – how they might co-opt some of those principles to help make this decision more approachable.

Additional information

Notes on contributors

Ed Moyle

Ed Moyle is currently Director of Emerging Business and Technology for ISACA. Prior to joining ISACA, Ed was Senior Security Strategist with Savvis and a founding partner of the analyst firm Security Curve. In his 15+ years in information security, Ed has held numerous positions including: Senior Manager with CTG’s global security practice, Vice President and Information Security Officer for Merrill Lynch Investment Managers, and Senior Security Analyst with Trintech. Ed is co-author of Cryptographic Libraries for Developers and a frequent contributor to the Information Security industry as author, public speaker, and analyst.