Pros and cons of using a vendor provided analytical data model in your BI implementation
The following question comes from many of our clients: what are some of the advantages and risks of implementing a vendor provided analytical logical data model at the start of any Business Intelligence, Data Warehousing or other Information Management initiatives? Some quick thoughts on pros and cons:
Pros:
- Leverage vendor knowledge from prior experience and other customers
- May fill in the gaps in enterprise domain knowledge
- Best if your IT dept does not have experienced data modelers
- May sometimes serve as a project, initiative, solution accelerator
- May sometimes break through a stalemate between stakeholders failing to agree on metrics, definitions
Cons
- May sometimes require more customization effort, than building a model from scratch
- May create difference of opinion arguments and potential road blocks from your own experienced data modelers
- May reduce competitive advantage of business intelligence and analytics (since competitors may be using the same model)
- Goes against “agile” BI principles that call for small, quick, tangible deliverables
- Goes against top down performance management design and modeling best practices, where one does not start with a logical data model but rather
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- Defines departmental, line of business strategies
- Links goals and objectives needed to fulfill these strategies
- Defines metrics needed to measure the progress against goals and objectives
- Defines strategic, tactical and operational decisions that need to be made based on metrics
- Then, and only then defines logical model needed to support the metrics and decisions
Thoughts, comments?