For Application Development & Delivery Professionals

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Executive Summary

Today, enterprises face increasing data integration challenges, largely because of growing data volumes, data protection issues, data migration complexities, the need for real-time information, integration of structured with unstructured data, and the limitations of existing data integration technologies. Business users want quick access to reliable real-time information to help them make better business decisions. As a result, information architecture and application development professionals find themselves on a never-ending quest to improve data's quality and timeliness. To provide insight into the vast array of options available to meet today's data integration challenges, Forrester investigated 11 technologies used to support a wide variety of data integration requirements, including change data capture (CDC), data access, data discovery, data quality services, data replication, data services platforms, distributed data caching, enterprise information integration (EII), enterprise services buses (ESBs), extract, transform, and load (ETL), and master data management (MDM). We found that data quality services, data services platforms, ESBs, and MDM continue to mature with widespread adoption, while CDC, data access, data replication, and ETL have reached the Equilibrium phase. Data discovery and distributed data caching are in the Survival phase, and EII stands alone in the Decline phase.

Keywords

• data
• data volume
• data protection
• data migration
• data quality
• data services

TABLE OF CONTENTS

• The State Of Enterprise Data Integration
• Why The Future Of Enterprise Data Integration Matters
• Overview: Forrester's TechRadar For Enterprise Data Integration
• Enterprise Data Integration TechRadar: A Mature But Growing Market

RECOMMENDATIONS

• Revisit Your Enterprise Data Integration Strategy
• Supplemental Material
• Related Research Documents

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