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Data Warehousing Failures

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Data Warehousing Failures
Data Warehousing Failures

Eight studies of data warehousing failures are presented. They were written based on interviews with people who were associated with the projects. The extent of the failure varies with the organization, but in all cases, the project was at least a disappointment.

Read the cases and prepare a one or two page discussion of the following:

1. What’s the scope of what can be considered a data warehousing failure? Discuss.
2. What generalizations apply across the cases?
3. What do you find most interesting in the failure stories?
4. Do they provide any insights about how a failure might be avoided?

Case Studies of Data Warehousing Failures

Auto Guys

Auto Guys initiated a data warehousing project four years ago but it never achieved full usage. After initial support for the project eroded, management revisited their motives for the warehouse and decided to restart the project with a few changes. One reason for the restructuring, according to the project manager, was the complexity of the model initially employed by Auto Guys. At first, the planner for the data warehouse wanted to use a dimensional model for tabular information. But political pressure forced the system’s early use. Consequently, mainframe data was largely replicated and these tables did not work well with the managed query environment tools that were acquired. The number of tables and joins, and subsequent catalog growth, prevented Auto Guys from using data as it was intended in a concise and coherent business format. The project manager also indicated that the larger the data warehouse, the greater the need for high-level management support – something Auto Guys lacked on their first attempt at setting up the warehouse. Another problem mentioned by the project manager was that the technology Auto Guys chose for the project was relatively new at the time, so it was not accepted and did not garner the confidence that a project

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