Data Quality, Governance and Compliance

О курсе

Build the essential competencies needed to ensure accuracy, reliability, and governance across modern data ecosystems with this comprehensive course on Data Quality, Governance and Compliance. You’ll learn how to validate datasets using arithmetic checks, reconcile data across multiple sources, and diagnose discrepancies through deductive reasoning. The course also explores how to design automated data quality dashboards, distinguish between SQL and NoSQL systems, and evaluate source models for feasibility. A significant portion of the curriculum focuses on metadata management and governance: you’ll learn how to enrich BI semantic layers using data dictionaries, establish and maintain data quality standards, and document information assets for clarity and consistency. Additionally, you’ll gain experience implementing secure data access procedures—such as service accounts and row-level security—to uphold compliance requirements. With modules from Google, Meta, LearnQuest, and IBM, the course blends practical ETL testing techniques, contextual analytical reasoning, metadata best practices, and governance frameworks. You’ll finish with the ability to manage BI solutions across their entire lifecycle, from deployment and optimization through long-term governance—making you a capable and trustworthy steward of enterprise data systems.

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