Fit Your Data Architecture To Your Analytical Needs
Forrester's Business Intelligence Data Architecture Decision Tool Helps You Make The Right Choice
July 9, 2009
Why Read This Report
Delivering business intelligence (BI) effectively depends on a data management architecture that fits your reporting and analytical requirements. Unfortunately, many data warehousing (DW) and BI professionals overlook the need to optimize an end-to-end data management architecture to support diverse BI applications. Well-designed data management architectures optimize such key infrastructure as data warehousing, data integration, data quality, metadata, and master data management. This foundational data architecture can improve — or if implemented poorly, constrain — the flexibility, scale, performance, and ultimately the anticipated ROI of your BI ecosystem. Forrester identifies and evaluates five analytical data architectures to consider, each with distinct advantages and drawbacks: distributed data marts, data federation, enterprise data warehouse, hub-and-spoke, and information-as-a-service (IaaS). Combined with Forrester's Business Intelligence Data Architecture Decision Tool, this report helps information and knowledge management (I&KM) pros determine which architecture is the best fit for their needs.
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Table of Contents
- Don't Shoehorn Analytic Requirements Into Ill-Fitting Architectures
- Fortunately, Data Architectures Can Be Designed To Fit Most Needs
- Using Forrester's Decision Tool As A Guide, Explore Your Options
- Supplemental Material
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