Establishing 'Making it Happen' as a 'Formal & Predictable' Discipline

DW Dimensional Modeling Concepts	DW Design & Architecture

Execution-MiH ENCYCLOPEDIA → Enterprise Intelligence → SECTION - Data-Warehouse/Mart →

CHAPTER -

DW Dimensional Modeling Process

This chapter takes over from previous chapter, and details on how we go about converting the concepts into deliverables.

Topics

Data Mart Business Theme Matrix in Data Warehouse Dimensional Model

The start point of business themes and the end delivery of data marts have to be linked to confirm that we have not missed any business themes.

Data Mart Dimension Fact table Matrix in Data Warehouse Dimensional Model

Going back-words, each data mart should list the dimensions and measures, to ensure that dimension and facts are fulfilling the information needs for a business theme.

Data Mart Fact Table Grain Matrix in Data Warehouse Dimensional Model

Data Mart typically has one to one link with fact table. The fact table grain is the most granular level of business event or entity which can provide the level of detail needed by Data Mart.

Derived Facts table in Data Warehouse Dimensional Model

With Data Marts mapped with facts and dimensions, its time to list the set of facts and the derived facts to be used ACROSS the data warehouse and data marts.

Derived Dimension Attributes Table

With Data Marts mapped with facts and dimensions, its time to list the entire set of dimensions and their attributes to be used ACROSS the data warehouse and data marts.

Dimensional Attributes+ Facts + Source System Matrix

With a clarity of data marts, dimensions and attributes, it time to cross over to design phase. First cross over is the mapping of the source systems to dimensions/Attributes and facts.