PHILADELPHIA, PA — Qlik has been named a Leader in the IDC MarketScape: Worldwide Data Integration Software Platforms, 2025 Vendor Assessment, a designation that reflects rising enterprise demand for real-time data movement, governed self-service access, and AI-ready data products across hybrid and multi-cloud environments.
IDC’s analysis highlights Qlik’s cloud-agnostic platform, which unifies change data capture with ELT/ETL processing, catalog-driven governance, and embedded generative AI assistance for data engineers. The research firm says these capabilities allow organizations to integrate, manage, and operationalize trusted data at speed—a growing differentiator as companies modernize their architectures.
“Data leaders want two outcomes at once—make trusted data available faster and keep architectures open and flexible,” said Drew Clarke, EVP of Product & Technology at Qlik. “We bring real-time movement, productized trust, and AI assistance directly into the data engineering flow.”
IDC notes that Qlik supports open lakehouse modernization through Apache Iceberg ingestion and optimization, while maintaining flexibility across SaaS, hybrid, and client-managed deployments on AWS, Azure, and Google Cloud. The report also cites Qlik’s embedded generative and agentic tools—prompt-to-SQL, pipeline documentation, rule suggestions, and API contract design—as enablers of more efficient engineering.
Stewart Bond, IDC’s vice president of data intelligence and integration software research, said Qlik’s leadership ranking reflects continued investment in capabilities that deliver “trusted, governed, and AI-ready data pipelines” for a variety of enterprise use cases.
Customers report similar benefits. Colton Porter, manager of advanced planning systems at MillerKnoll, said Qlik enables continuous data movement, clear lineage, and visible governance while helping teams modernize to Iceberg and incorporate AI assistance directly into workflows.
Qlik said it will continue expanding in-flight transformations, cross-cloud operability, and support for retrieval-augmented generation and vectorization as enterprises push to link high-quality data pipelines more directly to analytics and AI applications.
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