Data Management Foundations: Maintaining One Version of the Truth

Inconsistent data leads to conflicting reports, wasted hours of reconciliation, and poor business decisions. To drive reliable insights, organizations must establish and protect a single, accurate version of the truth. This text-based course guides you through the fundamental principles of modern data management, helping you align disparate data sources and streamline your reporting pipelines. You will transition from managing chaotic, siloed data to designing clean, centralized data architectures that support reliable decision-making. By understanding how to identify and remediate technical debt, you will build sustainable systems that maintain data integrity over time. What you'll learn: - Understand the core principles of data governance and the single source of truth (SSOT) framework - Identify and resolve technical debt in legacy data systems and pipelines - Establish clear data ownership and stewardship protocols across teams - Design robust data integration workflows that prevent duplicate or conflicting records - Apply modern data quality metrics and validation rules to maintain high-integrity datasets - Configure basic metadata management practices to keep your data definitions consistent This course starts with foundational definitions of data governance and technical debt, before moving into practical strategies for data alignment, clean integration pipelines, and modern quality control. You will learn through clear, written explanations and real-world scenarios designed for immediate application. This course is designed for beginner data analysts, project managers, and aspiring data engineers who want to build a solid foundation in data management. No prior database administration experience is required.