Why to build or create a data model?
- To avoid redundancy of data in a OLTP database.
- In Data Warehousing, data from source systems can be transformed as per the rules and loaded into target tables.
- In Data Warehousing, you can do data profiling by cleaning the data from source systems and load that into data warehouse columns. i.e. Same column from different source system may have different data structure and column name. In data warehouse, we can create a column as per standards and load the data.
- In Data warehousing, several columns data help in predicting the future, which is a part of data mining.
- In Data Warehousing or in Data Mart, you can drill down the data to a certain and you can get consolidated information. For example, with location dimension, You can group the data on a state level basis, county level basis, city level basis. With time dimension, you can drill down on a yearly basis or quarterly basis or on monthly basis.
- A new application for OLTP (Online Transaction Processing), ODS (Operational Data Store),
data warehouse and data marts.
- Rewriting data models from existing systems that may need to change reports.
- Incorrect data modeling in the existing systems.
- A data base that has no data models.
Advantages and Importance of Data Model:
- The goal of a data model is to make sure that all data objects provided by the functional team are completely and accurately represented.
- Data model is detailed enough to be used by the technical team for building the physical database.
- The information contained in the data model will be used to define the significance of business, relational tables, primary and foreign keys, stored procedures, and triggers.
- Data Model can be used to communicate the business within and across businesses.