Level: Beginner to Intermediate
Data is a critical resource for every organization. We depend on data every day to keep records, produce reports, deliver information, monitor performance, and make decisions. Data assets power BI dashboards, self-service analytics, data science projects, AI and machine learning, and more. The data resource is on par with financial and human resources as a core component of doing business, yet data management practices are often quite casual and unstructured. Data governance brings the same level of discipline and structure to data management as is typical when managing financial and human resources.
Building a data governance program is a complex process that focuses people, processes, policies, rules, and regulations on achieving specific goals for a managed data resource. Successful and effective data governance depends on achieving the right balance between control-oriented and collaborative governance to address the often conflicting needs of enterprise data management, self-service, agile development, big data, and cloud deployments.
This is part of an optional Data Governance Bootcamp. Learn more about the courses offered, or attend this individual course.
You Will Learn
- Definitions and dimensions of data governance
- Practices and techniques for building and operating a data governance program
- The roles, skills, and disciplines essential to data governance
- The importance of data stewardship to data governance success
- Activities, issues, and options when building a data governance program
- How to create the right balance of authoritarian and collaborative governance for the needs of self-service, agile development, big data, cloud services, and other modern practices
- Data governance professionals, including data stewards and data curators
- Data management professionals, including CDOs, BI managers, and data quality managers
- Data analytics professionals, including CAOs, data scientists, and data analysts
- Architects, data engineers, BI and analytics developers, data modelers
- Business stakeholders, compliance officers, risk management professionals, internal auditors