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Designing Data Governance from the Ground Up • Lauren Maffeo & Samia Rahman
Designing data governance from the ground up requires a people-centric approach, defining data domains, and fostering collaboration, automation, and continuous improvement to ensure data quality and usability.
- Focus on people over technology: Data governance is about people, processes, and tools. It’s crucial to engage stakeholders and employees in the data governance process.
- Define data domains: Identify key data domains and sub-domains to better understand and govern data.
- Start with a mission statement: Develop a clear mission statement for data governance that aligns with the organization’s overall mission.
- Automate and standardize processes: Implement automation and standardization to ensure consistency and efficiency in data governance.
- Foster collaboration: Encourage collaboration and communication across departments to ensure data governance is a team effort.
- Focus on usability: Prioritize usability and user experience in data governance tools and processes.
- Lead with why: Leaders should lead with “why” and align data governance efforts with the organization’s overall mission and goals.
- Data governance is not a one-time project: Data governance is an ongoing process that requires continuous effort and iteration.
- Focus on quality over quantity: Prioritize data quality over the sheer volume of data.
- Data governance should be a business-driven initiative: Data governance should be driven by business needs and goals, rather than technical requirements.
- Data stewards are crucial: Identify and empower data stewards who can oversee and manage data governance efforts.
- Governance driven development: A focus on governance-driven development can help ensure data quality and maintainability.
- Data as a product: Treat data as a product that needs to be designed, developed, and maintained.
- Focus on automation: Automate data governance processes as much as possible to reduce manual effort and increase efficiency.
- Continuous improvement: Continuously monitor and improve data governance efforts to ensure they remain effective and aligned with the organization’s goals.