7 Best Practices for Successful Data Governance Programs | 7wData

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data governance isn't about making the right decisions. It's about making decisions the right way.

As a practice, data governance has grown over the years from relatively simple policies for data security and privacy to a broad enterprise-wide initiative covering not only access to data, but also the application of data in business intelligence, analytics and machine learning plus the purpose of data for marketing, sales, research and so on.

While a better process typically leads to better outcomes, there's a risk if the systems of oversight for a data governance policy get tangled up with financial or productivity goals. Shortcuts are tempting, but they can compromise regulatory compliance, business reputation and operational effectiveness. Why effective data governance is important

The rise in governance awareness has coincided with the rapid growth in data privacy and protection legislation and regulations that primarily are being driven by public concerns over the misuse of personal and private information.

Good data governance is a useful policy in and of itself. Yet any governance program needs broad organizational support to be effective . If, for example, a data governance program is motivated to be on the right side of regulations, then compliance will likely be a company's first concern. Compliance should then address key issues, including what it will take to meet a regulation's requirements and whether the source of the regulation is a government, a professional body or an internal code of practice.

An ineffective data governance policy can lead to broken processes. But even a well-governed organization may not be fully compliant if it overlooks or misunderstands part of the regulation or doesn't keep up with rules changes. Just as governance and compliance are related but separate processes, so too are privacy and security. For example, a home without the window blinds drawn may lack privacy but might be relatively secure if the doors are locked. On the other hand, a home with the blinds drawn and doors unlocked may feel more private but less secure.

Therefore, even though data security policies within a governance program can make data privacy efforts easier, data privacy policies must include provisions for security protection.

Adhering to governance best practices can help promote greater confidence and trust in data quality, usage, privacy and security.

Data governance best practices to help you succeed

It's important not to overcomplicate data governance. At the same, data governance can't stand alone as a strategy within the enterprise. To develop and maintain a successful governance program and cope with the corporate anxiety associated with compliance , security and privacy issues, following are seven best practices that will help organizations play defense and still use data to achieve their financial and productivity goals without resorting to shortcuts.

1. Measure the success of your governance program

Data governance is about the process of making decisions, not the outcome of those decisions. It's also true that common business measures of success are not directly applicable. Metrics that can help track the success of a governance program and demonstrate that the organization is better informed, resilient and accountable include the following: the amount of people who are covered by the program -- those assigned specific tasks, trained in processes or made aware of policies; the number of data sources that have a related governance policy defined and applied to make operational, tactical or strategic decisions; and noted improvements in the quality and reuse of data .