1. Data Warehouse Data Mart Elahe Soroush

2. Agenda  Data Warehouse definition  Concepts  Logical transformation  Physical transformation  DW components  Disadvantages of DW  Data Mart  Benefits of DM  DW vs. DM  DM development  ECRM environment

3. Definition By Bill Inmon in 1990 : "A warehouse is a subject-oriented, integrated, time-variant and non-volatile collection of data in support of management's decision making process".

4. Definition(cont.)  Data warehouse “A data warehouse is a structured extensible environment designed for the analysis of non- volatile data, logically and physically transformed from multiple source applications to align with business structure, to use in Decision-Support and Executive Information Systems”.

5. Concepts "Warehousing" data outside the operational systems  Performance  Subject oriented  Integrating data from more than one operational system  Data is mostly non-volatile  Data saved for longer periods than in transaction systems

6.  Structured extensible data model Logical transformation of op. data

7.  Structured extensible data model  Data warehouse model aligns with the business structure

8. Logical transformation of op. data

9.  Structured extensible data model  Data warehouse model aligns with the business structure  Transformation of the operational state information  De-normalization of data  Static relationships in historical data

10. Physical transformation of op. data  Operational terms transformed into uniform business terms  Single physical definition of an attribute  Consistent use of entity attribute values  Issues associated with default and missing values

11. Business view summarization of data  Initial analysis in summary views  Significant performance gains  Many views into the same detail

12. DW Components

13. Business use of a data warehouse

14. Disadvantages of DW  Data warehouse takes time and more expensive to build  Data warehouse is more complicated on many aspects including the development,end-user training and difficulty in distributed database environment  Data warehouse has a considerable time-lag from current operation

15. Disadvantages of DW When the size of a data warehouse goes very large  The competition to get inside a warehouse grows fierce.  Data becomes harder to customize  The cost of doing processing in the data warehouse increases as the volume of date increases  The software that is available for the access and analysis if large amount of data is not nearly as elegant as the software that can process smaller amounts of data. Solution : Adding data marts to the decision support system

16. Data Mart Definition Small DW that contains user-specific data that has already been customized and summarized for a specific department within an organization, such as marketing, sales, finance, or accounting. Next step in data storage

17. Benefits of DM  it costs less  Supports individual knowledge worker communities  less likely to lead to interdepartmental conflicts  A department can customize its own data mart according to its own requirement  There is more options when selecting a suitable software for data mart as well as for data analytical

18. DW vs. DM

20. DM development  The top down model  The bottom up model  The parallel model  The parallel model with feedback.

21. ECRM environment