Part 4/12:
- Data Quality and Consistency: Ensuring data quality through rules, validation, and profiling intensifies complexity, especially when source data is unstructured or poorly documented.
Data Modeling in Practice: Patterns and Approaches
Organizations typically employ various patterns and models depending on the goals:
Platform Modernization & Data Enhancement: The majority of projects focus on modernization efforts and improving data quality, often employing approaches like relational models for transactional systems, dimensional models for analytics, and Data Vault for agility and scalability.
Modeling Techniques:
Relational Models: Best suited for transaction processing systems.
Dimensional Models: Used for analytical reporting and insights.