Most executives today want to run data-driven organizations, but few recognize how challenging it is to manage enterprise data. In most organizations, data is fragmented: it’s collected by dozens, if not hundreds of systems, and stored in multiple formats at different levels of granularity. Data is rife with errors caused by faulty data entry or systems hiccups, and it contains sensitive information that must be kept private and secure. Consolidating this data, either physically or virtually, is akin to piecing together Humpty Dumpty after his great fall.
Modern organizations need more than all the king’s men and horses to harmonize their enterprise data; they need a robust data governance program. When done right, a data governance program creates the roles, teams, policies, standards, processes, and workflows required to deliver trustworthy, consistent data, reduce errors, and address issues and risks in a timely manner. These guide the process of managing data through its lifecycle in accordance with policies and standards to support data-driven decisions and applications. (See figure 1.)
“A data governance program.… drive(s) the work of business and technical people who use and manage data to support data-driven decisions and applications.”
Sean Hewitt speaks about the difference between data management and data governance.