Small businesses with limited resources often struggle with the contact data quality tasks necessary for maintaining clean and accurate records of their customers or business partners. But as Leo King reports for ComputerWorld, it seems that major multinational corporations face similar challenges.

King writes that Paul Fulton, the vice president of data governance for Visa Europe, recently explained how his company made it a priority to organize, manage and derive value from the information coming in from all the transactions Visa processes every day.

The first step for most data governance projects will be to create policy and compliance measures, followed by "appointing the data stewards" to lead the charge in every department. From there, set up data definitions and run regular checks on the system.

Fulton acknowledged that address validation, list cleansing and other data quality functions were part of a "constantly evolving process." He suggested companies that want to launch their own DQ initiatives avoid the jargon that's usually associated with data management of any kind, since that can prove off-putting for the managers and employees involved.

"It's more productive to speak the language of the business, and if that means data protection, value from data or better management," he added. Although there is no set template for data governance, addressing the corporate culture and adopting contact data quality solutions are typically the main components.