Core Concepts of Data Modeling

Core Concepts of Data Modeling

1. Models are based on related tables of data. Defined numeric values are known as measures, the entities are known as dimensions. Conceptually, the model forms a multidimensional structure called cube, in which any point where the dimensions intersect represents an aggregated measure for them.

2. TABLES & SCHEMA

   • Dimension tables represent the entities by which we want to aggregate numeric measures. Each entity is represented by a row with a unique key value. Columns represent attributes of an entity.
     • The numeric measures aggregated by the various dimensions are stored in FACT tables. Each row in a fact table represents a recorded even with a numeric measure associated with it.
     • The schema of fact and dimension tables is used to create an analytical model where measure aggregations are pre-calculated.
       • STAR SCHEMA: where a fact table is related to one or more dimension tables.
   • ATTRIBUTE HIERARCHIES
     • Enable to quickly drill up/down to find aggregated values at different levels in a hierarchical dimesion.

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