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