A data governance framework defines how data is managed, protected and documented to ensure accuracy, compliance and controlled access across the organization.
What Is a Data Governance Framework?
A data governance framework is a set of rules and processes that determine how data is gathered, stored and used within an organization. These rules establish clear expectations around company data for all employees to follow, avoiding confusion and keeping a business’ data secure.
To succeed, a data governance framework must define clear roles and responsibilities to ensure confidentiality and security.
How Does a Data Governance Framework Work?
A data governance framework focuses on strong security measures to protect how data is managed and accessed. To maximize security, an organization must resolve issues like who has access to what data and who is in charge of enforcing data policies. These tasks could be given to a data governance team, IT and security teams or members across different departments, depending on the size and needs of the organization.
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. To carry out effective data retention policies, businesses must make sure they have the proper tech stacks and procedures in place. All employees should know who is responsible for storing and organizing data, how to do so with the tools at their disposal and any company guidelines surrounding this process.
Data deletion policies also directly address the issue of data security by enabling data to be removed or archived when it is no longer needed. The framework should perform all of the necessary security actions without hindering normal, productive workflows. Companies can measure the success of these policies and the framework as a whole by defining clear goals, such as lowering operational costs or accelerating daily processes.
How to 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 current data handling processes, data architecture, and roles involved in data oversight. 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), choose a governance approach that aligns with your organization’s culture — for example, a top-down model emphasizes centralized control and compliance, while a bottom-up model encourages broader participation and operational flexibility.
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.
Benefits of a Data Governance Framework
- Security: Knowing how data is stored and who can access certain data can prevent breaches and ensure all company data is accounted for.
- 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.
- Data compliance: With all employees understanding how data is stored and used, it becomes easier to stay in compliance with local, national and international laws.
- Enhanced cost-efficiency: A well-designed data governance framework can improve cost-efficiency by streamlining data workflows and reducing redundancies, though initial setup may require investment.
Data Governance vs. Data Management
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.
Frequently Asked Questions
What is a data governance framework?
A data governance framework establishes rules for how all data across an organization is collected, stored, accessed and used. Through this framework, a company can ensure its data is accounted for, secure and accessible to the appropriate personnel.
What are the pillars of data governance?
While there’s no universally agreed-upon set, common pillars of data governance include:
- Data stewardship (assigning responsibility for data assets)
- Data quality (ensuring accuracy and consistency)
- Data security (protecting data from unauthorized access)
- Metadata management (documenting data lineage and meaning)
- Compliance (ensuring adherence to legal and regulatory standards)
These pillars support effective data oversight across an organization.
