Business Intelligence Best Practices - BI-BestPractices.com

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2007 Best Practices Award Winner: Lawrence Livermore National Laboratory
LLNL's data warehouse is now a portal-based Java and Oracle RDBMS application considered highly successful in delivering accurate and timely information.

2007 Best Practices Award Winner: Ingenix
The consolidation of various data silos has saved the company several million dollars, and has produced ongoing cost savings, eliminated redundancies, and dramatically increased the efficiency of integrating new data sources.

2007 Best Practices Award Winner: Verizon Data Services
As a result of building its own analytical application, Verizon now has a single 360-degree view of the customer across all acquired brands and regions, and it operates with a single, common version of the truth for reporting and analysis.

2007 Best Practices Award Winner: StubHub
Since its founding in 2000, StubHub experienced triple-digit year-over-year growth, straining its existing information management infrastructure.

2007 Best Practices Award Winner: Richmond Police Department
Combining technology expertise from SPSS and Information Builders, the Richmond Police Department (RPD) is now using predictive analysis and business intelligence technology to apply information-based policy.

2007 Best Practices Award Winner: DaimlerChrysler AG
In a similar fashion, GPSIS is an SRM—Supplier Relationship Management—system that provides a basis for managing the company’s relationship to its suppliers.

2007 Best Practices Award Winner: UMB Bank
During a growth phase, UMB aligned their tools and technologies to fit their business model, which enabled UMB associates to become customer-centric.

The Business Intelligence ROI Challenge: Putting It All Together
by Bill Whittemore
Getting approval for your business intelligence (BI) or data warehouse project requires being able to demonstrate business value to your decision makers. Among the most difficult tasks is providing a predictable ROI to senior management.

Ten Mistakes to Avoid When Estimating ROI for Business Intelligence
by Evan Levy
The most common missteps managers make when financially justifying their business intelligence (BI) and data warehouse programs.

Data Warehousing ROI: Justifying and Assessing a Data Warehouse
by Hugh Watson, Dorothea L. Abraham, Daniel Chen, David Preston, Dominic Thomas
Drawing on the data warehousing literature, survey data, theory, and eight case studies, seven justification and assessment propositions are presented.

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