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.
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.
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.
How Does a Data Governance Framework Work?
A data governance framework is concerned with top-notch security requirements for data management systems. 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 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. 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 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:
- 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?
- 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.
- 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.
- 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.
What Are the 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: Data governance frameworks speed up the process of accessing and leveraging data, raising production and reducing operational costs.
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.
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?
There is no industry-wide agreement on the pillars of data governance, but several commonly referenced pillars are data stewardship, data quality, data management and data security.