The data integration tools market comprises stand-alone software products that allow organizations to combine data from multiple sources, including performing tasks related to data access, transformation, enrichment and delivery. Data integration tools enable use cases such as data engineering, operational data integration, delivering modern data architectures, and enabling less-technical data integration. Data integration tools are procured by data and analytics (D&A) leaders and their teams for use by data engineers or less-technical users, such as business analysts or data scientists. These products are consumed as SaaS or deployed on-premises, in public or private cloud, or in hybrid configurations.
Data virtualization technology is based on the execution of distributed data management processing, primarily for queries, against multiple heterogeneous data sources, and federation of query results into virtual views. This is followed by the consumption of these virtual views by applications, query/reporting tools, message-oriented middleware or other data management infrastructure components. Data virtualization can be used to create virtualized and integrated views of data in-memory, rather than executing data movement and physically storing integrated views in a target data structure. It provides a layer of abstraction above the physical implementation of data, to simplify querying logic.
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