Information Technology – 10 Myths about Data Warehousing
Debunking some common myths about data warehousing to bring the focus back to business
There are several reasons why data warehousing projects are expensive and fail to produce sufficient value for the business. I consider following 10 myths to be the main cause of the problem:
Myth #1 – A data Warehouse can create competitive advantage
Myth #2 – A data Warehouse is required for business intelligence
Myth #3 – Data Warehousing starting point is an enterprise data model
Myth #4 – You need both an Operational Data Store and a Data Warehouse to cover the entire spectrum of business reporting
Myth #5 – Data Warehousing requires an engineering approach
Myth #6 – Data Warehousing fails due to problems with transaction-processing systems
Myth #7 – We can’t predict what questions will be asked from a data warehouse
Myth #8 – Data Warehousing improves decision-making
Myth #9 – Data Warehousing empowers front-line and business staff to do their own analysis
Myth #10 – Data Warehousing reduces overall cost of reporting on business performance and opportunities
I’m sure that this will come as a sacrilege to those who have spent a career building their knowledge and practice of data warehousing. I’ve examined this topic in a lot more detail at A Myth Buster Anthology of Data Warehousing.
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