I have discussed about the Data Modeling in my previous article – What is Data Modeling ?
. I know most of you will be interested in knowing the modeling technique for data warehouse. Dimensional modeling is used for most of the data warehouse systems.
What is Dimensional Modeling ?
Dimensional modeling is the design concept used by many data warehouse designers to build their data warehouse. Dimensional Data Modeling is used for calculating summarized data. Dimensional modeling compromises of one or more dimension tables and fact tables.
Dimensional modeling is a technique for conceptualizing and visualizing data models as a set of measures that are described by common aspects of the business.
Dimensional modeling has two basic concepts :
- A fact is a measure or metrics of business process.
- A fact is a focus of interest for the decision making process.
- Measures are continuously valued attributes that describe facts.
- Facts are summarized historical and numerical data.
- A fact is a collection of related data items, consisting of measures.
- Dimensions are categories by which summarized data can be viewed.
- A dimension is a collection of reference information about a measurable event (facts).
- A “dimension” is essentially an entry point for getting at the facts. Dimensions are things of interest to the business.
- The parameter over which we want to perform analysis of facts
Dimensional Models are designed for reading, summarizing and analyzing numeric information, whereas Relational Models are optimized for adding and maintaining data using real-time operational systems.
Soon , I will write a detailed article about facts , dimensions, types of fact and dimension.
Thanks for reading