Data Modelling - How to ?

The Data Modelling is the most important activity in any BI project. A well planned Data Model helps to analyze the business performance in many perspectives.

The Data Modelling procedure stands the same for building Transactional (OLTP) and Analysis (OLAP) Database systems.

The Data Modelling for a Transactional databases systems are termed as Relational Data Modelling and for Analysis database systems as Dimensional Modelling.

It becomes important to understand that we need to add additional information in a Dimensional Model to accommodate aggregated relational data (also called as Facts) and group description data (also called as Attributes)

The relational data model is well normalized for effective read and write operations and designed in the 3rd Normal Form.

The dimensional data model is de-normalized for quick read only operations.

Both Normalized or De normalized  database systems require an effective Data Model for future maintenance and enhancements.

The following are the steps involved in an effective Data Model Process which is carried out sequentially.

1. Data Modelling Overview

2. Elements used in Logical Data Models

3. Physical Elements of Data Models

4. Normalizing a Data Model

5. Requirements Gathering

6. Interpreting Requirements

7. Creating a Logical Model

8. Common Data Modelling Problems

9. Creating the Physical Model in a Database System.

10. Indexing Considerations

11. Creating an Abstraction Layer in Database System.