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3 min read

How to Implement a Data Governance Framework

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Written by
Phil Guerin
Published on
February 22, 2023

A data governance framework is a high-level plan that outlines how an organization will manage and protect its data. It helps to ensure that all data is collected, processed, and stored in a consistent manner, and that only authorized users have access to it.

Implementing and maintaining a data governance framework can seem like a daunting task, but with the right planning and execution it can be a smooth process. With ever-evolving data privacy and protection requirements, having a successful data governance framework has never been more important to ensure the accuracy and integrity of your business’s data.

Whether you’re starting from scratch or revising an existing framework, going back to planning basics can ensure your framework meets your organization’s requirements today, and can scale with it in the future.

Guide to Data Discovery for Regulatory Compliance

Data protection boils down to having good security hygiene and baseline processes in place to guard your data. This guide is designed to help you organize and prioritize data security and best practice planning.

The first step is to ensure your data governance framework includes a clear and concise mission statement. This statement should outline the goals of the framework and how it will benefit the organization. Once you have created your mission statement, you'll need to establish governing policies and procedures. These policies and procedures will guide all aspects of data management within the organization.

Next, it’s time to appoint key personnel who will be responsible for implementation and enforcement. These individuals will be responsible for ensuring that all data within the organization is accurate, consistent, and safe from tampering or destruction. Finally, you must put into place systems and tools that will help facilitate efficient data management throughout the organization.

We’re breaking down several steps you can take and refer to as you build, revise and implement a data governance framework:

1. Define the goals of the framework

‍What do you want the framework to achieve? This could include things such as improving data quality, reducing compliance risks, or simplifying information management.

2. Assess your current situation

What kind of data do you have? Where is it being stored? Who has access to it? This exercise goes hand in hand with understanding your business’s attack surface. The amount of data your organization stores and shares outside the organization increases every day, which introduces new vulnerabilities and data governance challenges.

3. Create policies and procedures

Once you know what your goals are, you need to create specific policies and procedures for achieving them. These might include things such as requirements for data quality control, retention periods for different types of data, or methods for securing sensitive information.

4. Communicate the framework to all stakeholders

‍Make sure everyone who needs to know about the framework understands it and knows their responsibilities under it. This includes employees, contractors, suppliers.

5. Monitor and evaluate the results

The final step is to track progress against the goals set out in Step 1, make any necessary adjustments based on results achieved, and continue refining the framework over time.



A well-defined data governance framework is essential for any organization working to manage its data effectively. By following these simple steps, you can implement a successful framework that will meet your organization’s unique needs.

Data sprawl and unstructured data have changed regulatory requirements, which may affect existing data governance frameworks. If you’re looking for the latest data classification, retention and handling guidelines, or which regulations and frameworks apply to your business, check out this guide to data discovery for regulatory compliance.


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