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Limiting Business Intelligence Project Failures: Some Practical Hints, Part 2 |
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For any business intelligence (BI) project to succeed, proper project management guidelines, requirements gathering and expectations have to be created. In addition, because of the complexity involved in evaluating and purchasing a data warehousing and/or BI solution, businesses should develop an understanding of the architectural options available beyond what IT requires for development, testing and maintenance. Decision makers require this understanding to identify how data quality initiatives or data latency requirements will affect service level agreements as well as the integrity and value of the information and analytics being provided.
This article, a continuation of Part 1 of this series, discusses these concepts and looks at the importance of focusing on the customer, the benefits of developing broad-reaching BI initiatives, and how to tie these to project success.
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Limiting Business Intelligence Project Failures: Some Practical Hints, Part 1 |
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This two-part series provides some general hints into how organizations can limit the risk associated with their BI projects.
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Dysfunctions of a Business Intelligence Team: Lack of Trust |
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Background:
Note from Maureen Clarry: My recent article Dysfunctional Business Intelligence Teams discussed the high-level applicability of Patrick Lencioni’s (2002) The Five Dysfunctions of a Team to business intelligence (BI) teams. For the next five months, I’ve invited experts from our Knowledge Network to take a deeper look at each dysfunction in a series of separate articles. This month, James Wood will explore the first dysfunction – the lack of trust.
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IBM Cognos Customer Case Study |
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IBM Cognos BI solution helps Fabryo reduce inventories and increase customer satisfaction.
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Standing Up for Agile BI. (Sort of.) |
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Jill Dyché reconsiders her take on agile BI — for a second, anyway
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