Data Warehouse
Contents
Data Warehouse
Not in 3NF (Big Data)
- The data should be de-normalised to 2NF
- This means you get data redundancy
- This means you need more storage
- But you can get at the data more quickly
- The purposes of a DW is to provide aggregate data which is in suitable format for decision making.
Typical Data Warehouse Architecture
Staging / Integration Layer
- Create data in particular day
- Ensure all data comes from the same format
Data Warehouse / Data Vault
- All Data are having the same format
- Everything in 2NF
Data Marts
- Different department or team can have their dedicated Data Mart, with their own business logic applied.
- Provide information more quickly
- One user does data manipulation in his Data Mart will not affect other user in their Data Mart
ETL and Data Marts
- Extraction, Transformation and Loading
- Extraction. Get the Data
- Transformation. make it useful.
- Loading. Save it to the warehouse.
- Data Marts (Sub-sets of the Data Warehouse)
- Don’t mess with my data.
- Keep it simple for the user.
- Small problems are easier to solve