21st Century Data Governance

By Peter Marotta June 28, 2013

Peter Marotta  Strategies that businesses rely on for big data continue to evolve at breakneck pace. Many companies still follow the 20th century best practices: data stewardship, data and quality standards, and use of data management tools. Each of those things remains incredibly important for day-to-day operations. But it's also increasingly critical that companies go beyond managing the data itself and directly address how companies use it. Simply, we need to expand our view of data management to encompass data governance.

Dataversity, an online educational portal, recently released the preliminary results of a survey of about 250 business people in diverse jobs and industries. The results generally indicate companies are on the road to governance, though many seem to have a way to go. You may want to check it out to compare your company with the raw data available.

As I've noted before, data governance is rooted in the idea that the business is the caretaker of the information it manages. However, as the breadth, depth, and value of data increase, organizations need to take a still broader view. Data governance means directing people, processes, and information technology to be consistent and to handle and use information properly.

Also, as companies continue to tap external data resources, governance must extend beyond a company's walls and encompass data sourced by third parties. Working with a third party requires an even greater emphasis on data management and governance to ensure that partners adhere to the same standards as your own organization.

Organizations must build dynamic data management functions into their daily processes and turn their mindsets toward complete data governance to keep the quality of their data intact. That approach will allow them to focus simultaneously on future operational performance while minimizing costly errors.


Peter Marotta

Peter Marotta, enterprise data administrator, leads enterprise data management activities for Verisk Analytics. He focuses on documenting data assets, exploring methods for acquiring new and different data, supporting business unit plans, and promoting Verisk's enterprise data strategies.