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Principles and Rules Listing Page
Don't wait for universal models for Data Marting
While it is desirable to have the universal dimensions for individual data marts, one should not let a data mart project to get delayed even by a day for this purpose.
 
This page of 'Principles and Rules' is linked to:  Data Warehousing, Data Analysis/OLAP, BI platform Tools Evaluation,



The creation of universal and foundation dimensions (I.e. customer dimension is exactly the same across all data marts) is a long haul and it needs a cross functional and cross-process engagement. It is better to progress a show-case data mart so to get a sponsorship for a Data Warehouse initiative (which will include the creation of universal dimensions and measures).

There is a more intrinsic challenge. Sometimes even the customer dimension within a data-mart (say at a departmental level), becomes very fluid as complete thinking is not done on the dimension construct. This is due to co-ordination issue within the department (campaign managers vs sales lead managers within the sales function) and simple skills issues. This leads to a frequent demand for changes to the dimension.

The first step is therefore to have a good customer dimension (a low hanging fruit) within a data-warehouse before targeting the organization wide universal and consistent dimensions.

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Principles & Rules → Data Warehouse application is not limited to Analytics → Principles & Rules → Store as much detailed and granular data in data warehouse as possible → Principles & Rules → Data Normalization is not the best approach in Dimensional modeling → Principles & Rules → Keep the same names and definitions for all data elements → Principles & Rules → You cannot have a super-flexible Data warehouse → Principles & Rules → Dimensional models can be extensible and scalable → Principles & Rules → Data Marts should be ideally based upon a business process and not on a department. → Principles & Rules → Business Intelligence competency groups should be well-linked with business → Practice Techniques → Aggregation Queries on slowly changing Dimensions → Practice Techniques → Documenting your data-integration system → Principles & Rules → For a Data Warehouse/Data-Mart solution, analyze well, but be decisive → Principles & Rules → Maintain a trail of the key dimensional elements from source system to loaded → Principles & Rules → Conformed dimensions are must for cross-drilling → Practice Techniques → Checksum Approach for identifying the changed records from source systems → 
 
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