Data is an essential tool today. Whether you run a local book store or have a well-established organization with hundreds of people working for you, every business uses various forms of data. This data can generate new revenue sources, give the upper hand against competitors, and operate the company’s essential functions. This saved data in high volume is the key to their customers, and the quality and usage of this data can affect how the brand performs. Data governance structures exist in organizations to ensure the data provided to the company is relevant, accessible, and of high quality.
Here is how you can structure data governance to build a strong analytical action for your business-
What is a Data Governance Structure?
Data governance includes tasks that focus on keeping collected data usable, understandable, and protected for the business. Data governance is usually handled by a team of data analytics companies that answers any issue related to the data and ensures its safety. The data governance structure is a framework that connects employees to your company’s various technologies, clients, and operations.
What are the Components of a Typical Data Governance Structure?
Effective data governance is essential for a company’s overall growth and requires rethinking the entire organizational design. A typical three-tiered data governance structure includes these primary components-
#1- Central data management office: A chief data officer (CDO) leads the data management office (DMO). This team of targeted data strategy and governance leaders establishes the overall direction and standards for using, managing, and protecting data in the company.
#2- Data domain leaders: The everyday tasks are handled by the data domain leaders. They also organize data governance roles.
#3- Data Council: They are responsible for bridging the gap between the chief data officer (CDO) and data domain leaders. They connect the data strategy and priorities to corporate strategy. They also approve funding and address data governance and management issues with analytic data consultants.
How to Structure Data Governance?
Step #1- Establish a plan: The first step to creating an effective data governance structure is to establish a plan by discussing various terms with the team members, stakeholders, and others involved in the project. The basic design will include a mission statement, different goals, standards, and the reach of these standards. It will also name the authorities that can use the data for various purposes.
Step #2- Select a data governance model: Various data governance models have different concepts. Choosing a suitable model is crucial as not every model can fit every organization.
Step #3- Determine organizational hierarchy: The hierarchy in organizations ensures data strategies of the entire company are executed within its databases and systems. There can be two types of order- centralized and federated governance data.
Step #4- Distribute the data governance policies: Embed them into your employees’ everyday lives and operations to ensure they follow them. Encourage knowledge-sharing and create processes regarding policy usage for your employees to improve their efficiency.
Step #5- Identify potential risks: Cybercrimes are increasing, and it is necessary to keep sensitive data securely in organizations. It is best to identify the potential risks like excess access to the data and secure storage options to avoid them.
Step #6- Constantly adapt your framework: Businesses grow and change. Your data governance framework should also adapt and evolve to keep pace. Data and analytics consulting companies–
- Measure data usage
- Check data quality
- Determine policy conformance
- Analyze curation
