Data Governance Tutorial Notes

Introduction to Data Governance

• Speaker: Jen, an analytics professional
• Purpose: Discuss what data governance is, its importance, and distinctions between good and poor governance.

Definition of Data Governance

• What is Data Governance?
  • Rules, processes, and accountability surrounding data.
  • Ensures routine data usage, harmonization of sources, and proper access control.
  • Involves data ownership and responsibility for data accuracy and management.

Goals of Data Governance

• Ensure the right people have access to the right data in an efficient manner.
• Avoid multiple databases with the same information.
• Maintain consistent understanding of access rights and responsibilities.

Difference Between Data Governance and Data Management

• Data Governance: Outlines the framework, rules, processes, and accountability. Focuses on "what" and "how."
• Data Management: Implements rules and day-to-day operational tasks to adhere to governance.

Importance of Data Governance

• Quality data must be accessible only to authorized users.
• Prevents data duplication and unauthorized access.
• Facilitates efficient data usage across the organization.

Starting Data Governance: Key Considerations

Identify Involved Roles

1. Data Owners/Sponsors: Responsible for data accuracy and accountability. Typically higher-level staff overseeing specific data types.
2. Data Stewards: Subject matter experts who manage the data on a daily basis.
3. Data Champions: Individuals who advocate for data governance across the organization.
4. Data Governance Committee: Resolves conflicts and standardizes data usage and access across the organization.

Define Scope of Governance

• Narrow Focus: Start with critical areas, such as regulatory compliance rather than attempting to govern everything at once.
• Prioritization: Address the most significant issues first (e.g., compliance, urgent business needs).

Practical Steps in Implementing Data Governance

1. Document Data Sources: Identify available data, its owners, usage, access, and update frequency.
2. Understand Current Usage: Gather insights on how data is being used to inform governance decisions.
3. Establish Data Mapping: Create relationships between different data sets to provide a comprehensive view.
4. Manage Metadata: Maintain clear descriptions and formats of data to enhance understanding and usability.
5. Ensure Data Integrity: Maintain accuracy, validity, and consistency throughout the data lifecycle.

Ongoing Governance and Quality Assurance

• Continuous Monitoring: Data governance is not a one-time task; it requires periodic review and updates as business needs and data grow.
• Adaptability: Be prepared to adjust rules and processes as the organization and its data landscape evolve.

Conclusion

• End Goal: Establish rules and policies that ensure the right people access the right data at the right time, ensuring data quality and integrity.
• Call to Action: Encourage viewers to share and engage with the content for further learning on data governance.