A data governance framework ensures data is protected and well documented for the company to access as needed. In order for a governance framework to succeed, it needs to encompass all planned, sensible, functional roles and responsibilities necessary to keep data confidential and secure within your organization’s data system. 

How Does a Data Governance Framework Work?

A data governance framework is concerned with top-notch security requirements for data management systems. Data retention policies are implemented by the governance framework to determine how to securely store data. These policies handle where data is stored and archived, what data needs to be stored, and how long data stays in the database. Data deletion policies also directly address the issue of data security by enabling data to be related or removed if it’s not actively being processed. The framework should perform all of the necessary security actions without hindering normal, productive workflows. 

The goal of a data governance framework is to ensure data security. Keeping important data away from unauthorized users is essential to establishing appropriate boundaries around the data management system. Once all roles and responsibilities have been assigned, the framework issues ownership of selected snippets of data to users. While pieces of data may be viewable to some within the organization, that exact data may be inaccessible to others who may not have been granted the same security clearance. This is an effective way to keep data secure at all times. 

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How Do You Create a Data Governance Framework?

While these frameworks can be built individually, it’s best to create your framework with a team of accredited professionals. For the best and most effective result, compile a group of stakeholders across multiple disciplines, like IT personnel, cybersecurity experts, company executives and others. Data governance frameworks aren’t a one-person job; you’ll need cross-functional cooperation. 

To get started on your data governance framework, follow these essential steps: 

  1. Determine a strategy: Start by evaluating your company’s current database processes, qualified employees and productive workflow. Is there anything that can be reassessed and improved? Are there any safety concerns you’d like resolved?
  2. Start simple and small: With a strategy in place, identify a small database problem your team finds annoying. As beginners, you’ll want to start with small tasks to prepare for larger obstacles.
  3. Choose the right framework: Once you identify the problem(s), decide which data governance framework is most suitable to your company and its needs. A framework can be top-down and prioritize control of data to optimize data quality; or, a framework can be bottom-up and have ready access to data to optimize user productivity and workflow. 
  4. Update the framework: As your business evolves and grows, it’s important to keep your framework updated to adjust to larger data sets and more company users. 
Establishing Data Governance Framework. | Video: Informatica Support


What Are the Benefits of a Data Governance Framework?

While security may be the top benefit of this framework, there are other qualities worth mentioning. 

  • Flexibility: Data governance frameworks are incredibly flexible because they allow for individual and team usage while maintaining effective security measures. 
  • Data Storage: Data will be organized and easily accessible in set locations, so there will be little confusion regarding business operations. 
  • Undisrupted Performance: While the framework will be constantly running to safely handle and process data, you can still use the database and its assets to the fullest extent. 

Your company will prosper under an effective governance framework based on these benefits alone, not to mention the added security measures to give you peace of mind. 


Data Governance vs. Data Management: What’s the Difference? 

While data governance and data management often go hand-in-hand, they are distinct practices. Data management is an IT practice that collects, maintains and uses data securely and effectively. It’s what an organization does across the data’s life cycle. Data governance policies are practices that describe how data is processed in the management system to assure quality, privacy and compliance. Strong data management and data governance policies should be paired together for the best possible result, but it is possible to have data management without data governance policies. However, data governance frameworks are always recommended for organizational security.

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