Data Governance Framework: Definition and Critical Factors

A data governance framework creates a single set of rules and processes for collecting, storing, and using data. By doing so, the framework makes it easier to streamline and scale core governance processes, enabling you to maintain compliance, democratize data, and support collaboration—no matter how rapidly your data volumes grow.

With a data governance framework, you can ensure that your policies, rules, and definitions apply to all your data across your entire organization.

The ultimate objective of data governance is to generate the greatest possible return on data, capturing critical opportunities to leverage data assets while avoiding the risks of exposing them. These are the critical factors to consider as you assess your data governance readiness and maturity:

People. People collaborate on determining the technical requirements, defining the processes, and ultimately driving the data governance outcomes that support strategic drivers. Are your people committed to data governance? Have you formally defined their roles and responsibilities? Do they have the necessary skills? Have you developed a change management plan, including sponsors, to support organizational alignment and buy-in?

Processes. Data governance processes allow people to confirm that your data is formally managed across the enterprise, which ensures that your critical business processes draw on trusted data. Are your data definitions, rules, and goals realistic and appropriate? Are your business processes modernized and your business rules reviewed so that they can integrate data governance cleanly and deliver meaningful results?

Contributors. Business and IT subject matter experts who provide necessary context, including business leaders, process owners, and stewards who run the upstream and downstream processes impacted by your initiative, as well as IT architects, analysts, and systems experts

Technology. Technology includes the platforms, tools, and subject matter expertise necessary to enable a sound data governance process. Even if your existing systems are already governed to some extent, platform technology enablers such as data profiling, lineage, and metadata tools are critical to automating and scaling your data governance processes and accelerating time to value.