Data Intelligence and Integration Software

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Meet the Experts

Photo of Stewart Bond
Stewart Bond

Vice President, Data Intelligence and Integration Software



Data Intelligence and Integration Software enables the access, blending, movement, and integrity of data among multiple structured and semistructured data sources in hybrid and multicloud environments. The purpose of data integration is to ensure the consistency of information where there is a logical overlap of the information contents of two or more discrete systems. The purpose of data intelligence is to help organizations get answers to the five Ws of data: who, what, when, where, and why, plus how to inform data workers with the knowledge required to be more effective and efficient in data activities and inform organizational processes of data enablement through governance. Technologies include, but are not limited to, data connectivity, ingestion and transformation, change data capture (CDC), format and semantic mediation, data federation and virtualization, data quality and profiling, master data management, metadata management, and information life-cycle management technologies. This service also provides intelligence about streaming data integration and analytics.


Markets and Subjects Analyzed


  • Data ingestion and transformation software
  • Dynamic data movement software
  • Data quality and observability software (data profiling, cleansing, and deduplication for any data and domain-aware regularization data for such domains as customers, addresses, and products)
  • Data access infrastructure software (connectors and adapters that provide access to data within repositories)
  • Composite data framework software (intermediate software buffering apps from data sources supporting federated and virtual databases)
  • Master data intelligence software (software that defines, and controls data used for master data management solutions)
  • Metadata management software (provides the functionality to catalog and discover data and define schema, lineage, relationships, and business terms of structured and semistructured data)
  • Application of data intelligence software in support of data governance, data quality management, data sharing, and self-service
  • Data life-cycle management software to manage data life cycles from creation through to archival and destruction, including functions of test data management and data masking
  • Streaming data pipeline and processing software used for streaming data integration and analytics

Core Research


  • Worldwide DII Software Market Forecast and Vendor Shares
  • End-User Best Practices
  • Survey Results
  • Emerging Technologies
  • Market Analysis Perspective
  • Vendor Profiles
  • Case Studies
  • Future Predictions

In addition to the insight provided in this service, IDC may conduct research on specific topics or emerging market segments via research offerings that require additional IDC funding and client investment.


Key Questions Answered


  1. What makes the data integration and intelligence (DII) software market?
  2. What is the size and forecast growth rate of the DII software market?
  3. What are the emerging trends in the DII software market?
  4. Which are the major vendors and emerging players in the DII software market?
  5. What are the key and user pain points and challenges when it comes to DII solution implementation?