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October 9, 2006

Multidomain Data Warehousing Governance Must Balance Business Authority With Expertise

Data warehousing initiatives increasingly span multiple business domains to meet organizations' strategic goals, but project teams encounter difficulties in providing accurate and complete functional specifications. Extending requirements across domains inevitably increases the challenge by provoking cross-domain disagreements — making it critical to involve individuals with the authority to resolve those disagreements. Forrester recommends a business data governance model with three roles — the sponsor, the diplomat, and the guru — to maintain the proper balance of authority and expertise so that organizations can specify requirements with minimal iteration that align with their goals.

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Turning Transactions Into Decisions

Data integration techniques such as extract, transform, and load (ETL); enterprise information integration (EII); change data capture (CDC); and even custom-coding play a significant and perhaps the most critical role in delivering operational business intelligence (BI) capability. The key issue for data architects and BI app developers to keep in mind is the need to map these data integration options against the primary characteristic requirements of operational BI apps, such as tolerance for latency, unique data sources, decision-making time frame, data volume and quality, and cost of ownership. Also note: Employing only one of these techniques may do more harm than good; you must look at the total picture.

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