Data modeling

Data modeling (en-US)

Data modeling is the process of designing how data is structured, organized, and related so it can be stored, accessed, and used effectively. It helps teams define what data exists, what it means, how it connects across systems, and what rules govern it. Common goals include improving data quality, reducing ambiguity, enabling consistent reporting, and supporting application development and analytics. Data modeling also clarifies constraints (such as required fields, valid value ranges, and uniqueness) and documents business concepts in a form that engineers and analysts can implement. Typical approaches include: - Conceptual modeling: high-level entities and relationships (e.g., Customers, Orders). - Logical modeling: more detailed structure and relationships without tying to a specific database technology. - Physical modeling: implementation details such as tables, indexes, keys, and storage characteristics. Artifacts often include entity-relationship diagrams (ERDs), schemas, and data dictionaries. Good data models are designed for change—so they can evolve as business requirements grow—while maintaining integrity and performance.