In this topic, I learned about the importance of having a data warehouse, it is able to provide a comprehensive pool of data from both operational and external sources, also the various differences between DBMS, OLAP and DM. (Data Warehouse v/s Data Mart)
Characteristics of Data Warehouse Data
- Subject-Oriented
- Integrated
- Aggregated
- Historical
- Time Variant
- Non-volatile
- Denormalised
3 types of Schemas
- Star schema (http://ycmi.med.yale.edu/nadkarni/star_schema.bmp)
- Snowflake schema (http://www.bipminstitute.com/dipm_images/DDB2-%20Snow%20Flake-Schema.jpg)
- Constellation schema (http://etl-tools.info/images/dw_constellation_schema.jpg)
- Choosing the data mart
- Choosing the table granularity
- Identifying and confirming the dimensions
- Choosing the facts
- Storing pre-calculations in the fact table
- Rounding out the Dimension Tables
- Choosing the Duration of the database
- The need to track slowly changing dimensions
OLAP Cube
Types of Cube
- Relational OLAP (ROLAP)
- Multidimensional OLAP (MOLAP)
- Hybrid OLAP (HOLAP)
Typical OLAP Operations
- Roll up
- Roll down
- Slice & dice
- Pivot
- Drill accross
- Drill through
Design Strategies
- Top-down DW design
- Bottom-up DW design
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