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Data Warehouse fundamentals-Part 3


OLTP

  • application oriented
  • detailed
  • accurate, as of the moment of access
  • serves the clerical community
  • can be updated
  • requirements for processing understood before initial development
  • compatible with the Software Development Life Cycle
  • performance sensitive
  • accessed a unit at a time
  • transaction driven
  • control of update a major concern in terms of ownership
  • high availability
  • managed in its entirety
  • non redundancy
  • static structure; variable contents
  • small amount of data used in a process


 OLAP

  • subject oriented
  • summarized, otherwise refined
  • represents values over time, snapshots
  • serves the managerial community
  • is not updated
  • requirements for processing not completely understood before development
  • completely different life cycle
  • performance relaxed
  • accessed a set at a time
  • analysis driven
  • control of update no issue
  • relaxed availability
  • managed by subsets
  • redundancy
  • flexible structure
  • large amount of data used in a process
OLTP
OLAP
Contains Current Information
Contains previous + current information
Used to Run business
Used to analyze business
Data is updated and deleted
Data are only read
Size is less than 2TB
Size is more than 2TB

OLAP has 4 types
  1. DOLAP (Desktop OLAP): Ex: FoxPro
  2. ROLAP (Relational OLAP): Ex: RDBMS (Tables)-BOXIR2, COGNOS (Analysis)
  3. MOLAP (Multi Dimensional): Ex: Cubes, BOXIR2, COGNOS (Tools)
  4. HOLAP (Hybrid OLAP): ROLAP+MOLAP.
Data Modeling: Designing database/tables.

There are many types of data modeling but we use only 2 types.
  1. Entity relationship (E-R) Model: cannot allow to store duplicates values
  2. Dimensional Model: Allow Duplicate values.

Dimensional modeling has 3 phases.
  1. Conceptual Modeling: We are analyzing number of tables and columns.
  2. Logical modeling: Once tables are created, we are going to relate tables.
  3. Physical modeling: We are moving all schema’s/tables to data warehouse

NOTE:
SCHEMA- Collection of fact table and dimensional table.


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