Inmon vs Kimball – is this dispute outdated ?

Posted: March 2007 C: Business Intelligence Posted by: K. Panayotakis

Checking the popular keywords on my blog, I have noted that the ‘Inmon vs Kimball’ debate is still alive.

Many people researching on data warehouse architectures and relevant literature, realize that there are conflicting approaches and no globally accepted standard. Both approaches are still followed and supported by integrators and there are certain signs of convergence (e.g. in a dimensional approach, a Customer dimension which by itself is a complex DWH repository , not a single relational table).

However, is this the only problem to solve when building a BI infrastructure ? The answer is definitely no.

Architectures and tools are only a piece on the BI puzzle. Other BI issues seem to take the lead in today’s complex multichannel enterprises.

Defining an efficient reporting mix for various BU’s and hierarchical levels. Top management dashboards differ from line management reports.
The analytics to be used (segmentation techniques, value rankings, propensity modeling, recency, RFM, etc) should be adopted to the business goals and may differ according to the market/product and Customer segment.
Data source assessment & limitations (e.g. the ability to produce the ‘Customer holistic view’). Data quality and data enrichment (external sources, Customer /market surveys) issues arise.
The web channel which is emerging and gaining steadily a higher share of enterprise transactions throughout the value chain, is going to play an increasingly important role in the future BI infrastructures. Web analytics are differentiated from conventional BI, since they allow new types of analysis (e.g. keyword analysis, path analysis, referrer analysis). Web analytics issues: e.g. data quality & capture, web data integration on a unified repository, have to be tackled.
Convergence of structured and unstructured data, as business intelligence and/ or customer intelligence sources.
(last but not least) The analysis challenge: going beyond static reporting yielding limited business value to insightful analysis (also called the issue of actionability: producing actionable insight). The high need of capable business analysts (check this piece on great analysts).