Please enable JavaScript.

Coggle requires JavaScript to display documents.

DBW_general, C2: Bulding Block, C5: Defining the business requirement,…

- - - - allow for analysis of the PAST
      - relates info to the PRESENT
      - enable forecast for the FUTURE
- - - - heading of column
      - underlying basic of method for DW requirement definition
    - - bottom session
      - the number the users analyze
- - - - Available data souce
      - data structures within the data source
      - location of the data source
      - OS, network, protocols & client architecture
      - Data extraction procedures
      - Availability of history data
    - - sufficient details about storage requirement
      - estimate how much historical & archived data need
      - number of data mart
      - type of aggregation kept in dbw
    - - list data source
      - list relevant data structure
      - describe the merging, conversion, splitting
        before moving data into BDW
    - - drill-down analysis
      - roll-up analysis
      - drill-through analysis
      - slicing & dicing analysis
      - ad hoc report
      - online monitoring tools
        
        dashboards
        
        scorecards
- - - - key component of START schema is the set of dimension tables
      - inside is
        
        Dimension table key
        
        Large number of attributes (wide table)
        
        Textual attribute
        
        attributes not directly related
        
        flattened out, not normalized
        
        ability to DRILL DOWN/ DRILL UP
        
        multiple hierarchies
        
        less number of records
    - - inside is
        
        Concatenated fact table key
        
        Grain or level of data indentified
        
        Fully additive measures
        
        Semi-additive measures
        
        Large number of records
        (table deep, not wide)
        
        Only a few attribute
        (not wide)
        
        Sparsity of data
        
        Degenerate dimentions
      - The Factless Fact table
    - - easy for users to understand
      - optimizes navigation
      - most suitable for query processing
    - - Primary key
        (of dimension table)
      - surrogate key
      - foreign key
        (in fact table)
- - - - number and extent of data source
      - data granularity & data volumes