For Information & Knowledge Management Professionals

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September 25, 2006 Turning Transactions Into Decisions Data Integration Optimization For Operational BI by Rob Karel, Keith Gile with Connie Moore, Lucy Fossner	Average: 10  (1 rating)

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Executive Summary

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.

TABLE OF CONTENTS

• Decision Points And Decision-Making

RECOMMENDATIONS

• Many Data Integration Options Exist For Operational BI Apps

WHAT IT MEANS

• Many Data Integration Options Are Required To Satisfy All Of Your Needs
• Supplemental Material
• Related Research Documents

This is an excerpt