In a recent article by Wayne W. Eckerson, Director, TDWI Research, entitled “Operational BI: Sorting Out Your Options”, the options are given for providing near realtime business intelligence. The point of the article seems to be that you can have your BI either fast or of high quality, but not both. Given that a [...]

In the early part of 2007, Neil Raden wrote an article entitled “Business Intelligence 2.0: Simpler, More Accessible, Inevitable”. In this article, he argues that the a data warehouse (BI 1.0) is a big, slow, expensive machine for cranking out analytical data, and when it does, the data is highly-structured, only allowing a rigidly defined set of of questions to be answered. He continues that in the day of doing Google searches and social network…

Back in 2008, I was working for a telco in the Dominican Republic, consulting for their data warehouse team. I proposed a complete re-architecture of the data warehouse and the reporting platforms that the data warehouse supported. When I had to cost out the project, I had to include some hardware, primarily for the Ab Initio ETL tool we were going to migrate to, but also for the development and test servers, and more tape backup machines. All in all, the tab for the entire project grew to almost 2 million USD. It was just another reminder to me of how expensive a data warehouse can be…

It is quite obvious that there is no lack of innovative IT development processes, when one browses through the literature and blogs about software development methodologies. Few are those who would defend the waterfall approach …

In a previous post, I mentioned that one of the impacts of implementing a master data management system was removing some or all of the data integration responsibilities from the data warehouse. Since the data warehouse is the usual place for data integration, in particular customer data integration, I would like to explain myself and see if you agree, or at least see my point of view…

In organizations where the data warehouse has not reached full maturity, which is pretty much the bulk of them, the data warehouse still operates as a department level. This means that the data warehouse was not designed from the ground up to serve the enterprise …