Data Warehousing
A single, complete and consistent store of data obtained from a variety of different sources made available to end users in a what they can understand and use in a business context.
Definition : A process of transforming data into information and making it available to users in a timely enough manner to make a difference.
A data warehouse is a
Data Warehouse Architecture
A single, complete and consistent store of data obtained from a variety of different sources made available to end users in a what they can understand and use in a business context.
Definition : A process of transforming data into information and making it available to users in a timely enough manner to make a difference.
A data warehouse is a
- subject-oriented
- integrated
- time-varying
- non-volatile
Data Warehouse Architecture
Why Do We Need Data Warehouses?
Data Warehouse Life cycle
Application Areas
Industry
Ø Finance
Ø Insurance
Ø Telecommunication
Ø Transport
Ø Consumer goods
Ø Data Service providers
Ø Utilities
Application
Ø Credit Card Analysis
Ø Claims, Fraud Analysis
Ø Call record analysis
Ø Logistics management
Ø promotion analysis
Ø Value added data
Ø Power usage analysis
- Consolidation of information resources
- Improved query performance
- Separate research and decision support functions from the operational systems
- Foundation for data mining, data visualization, advanced reporting and OLAP tools
Data Warehouse Life cycle
- 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
- 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 data into the warehouse
- Install front-end tools
- Reporting tools
- Data mining tools
- GIS
- Etc.
- Test and deploy
-
Usability tests
- Software installation
- User training
- Performance tweaking based on usage
Application Areas
Industry
Ø Finance
Ø Insurance
Ø Telecommunication
Ø Transport
Ø Consumer goods
Ø Data Service providers
Ø Utilities
Application
Ø Credit Card Analysis
Ø Claims, Fraud Analysis
Ø Call record analysis
Ø Logistics management
Ø promotion analysis
Ø Value added data
Ø Power usage analysis