Data Warehouse is a special database that contains institutional and departmental data. Data warehousing has become an important technology even for small to mid-size companies for data analysis. One of the issues we encounter with data warehouses is
performance, since we combine large amount of data from multiple data sources.
A Data Warehouse Is A Structured Repository of Historic Data. It Is Developed in an Evolutionary Process By Integrating Data From Non-integrated Legacy Systems.
It Is Usually:
- Subject Oriented
- Integrated
- Time Variant
- Non-volatile
Development of a data warehouse includes development of systems to extract data from operating systems plus installation of a warehouse database system that provides managers flexible access to the data.
Steps for Building a Data Warehouse –
Analysis
- Identify- Target Questions, Data needs, Timeliness of data, Granularity
- Create an enterprise-level data dictionary
- Dimensional analysis
- Identify facts and dimensions
Design
- Star schema
- Data Transformation
- Aggregates
- Pre-calculated Values
- Pre-calculated Values
- HW/SW Architecture
Import Data
- Identify data sources
- Extract the needed data from existing systems to a data staging area
- Transform and Clean the data
- Resolve data type conflicts
- Resolve naming and key conflicts
- Remove, correct, or flag bad data
- Conform Dimensions
- Load the into the warehouse
Test and Deploy
- Usability tests
- Software installation
- User training
- Performance tweaking based on usage
