Trends Report

Fit Your Data Architecture To Your Analytical Needs

Forrester's Business Intelligence Data Architecture Decision Tool Helps You Make The Right Choice

July 9th, 2009
Boris Evelson, Vice President, Principal Analyst
Boris Evelson Vice President, Principal Analyst
Rob Karel, null
Rob Karel
With contributors:
James Kobielus , Connie Moore

Summary

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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