Qlik, software development company, delivers a comprehensive, cloud-agnostic data integration platform that spans real-time ingestion and replication, batch ETL/ELT, data quality, data productization, and governed self-service access for analytics and AI.
In the past, data integration was largely about moving information from A to B: ingestion, transformation, loading. But in the age of AI, that plumbing alone doesn’t cut it anymore. The real challenge — and the real opportunity — is in building a trust layer beneath those pipelines, one that guarantees the data feeding analytics and AI is fit, governed, and ready.
Organizations are investing in AI models, generative engines, dashboards, and self-service analytics; but time and again, progress stalls. Why? Because the foundation is weak: the data flowing into those systems isn’t consistently reliable, cataloged, or trusted.
When data is inaccurate, lacks lineage, or is stuck in silos, AI doesn’t generate value; it creates risk, rework, and confusion. In contrast, when we treat data as a product — with clear ownership, quality metrics, and built-in governance — AI becomes repeatable, explainable, and scalable.