Leaders in the data preparation market include Alteryx, Databricks, Dataiku, Domo, and ThoughtSpot.

MIAMI, July 14, 2026 /PRNewswire/ -- In 2026, data preparation has expanded beyond readying data for dashboards to producing the governed, AI-ready datasets and context that analytics and AI agents depend on. With data readiness emerging as the primary constraint on enterprise AI, organizations increasingly prioritize preparation that delivers trusted, well-governed data over the choice of any single model. Automation has advanced from suggesting transformations to executing them, and agentic preparation, in which systems plan a transformation, run it, and correct themselves, is emerging as the leading capability now that natural-language transformation is generally available across much of the market.

Automation is reshaping how data is prepared. Platforms now profile, cleanse, classify, and transform data with minimal user intervention, reducing the time required to make information available for reporting, analytics, and operational workflows. AI-assisted transformation, anomaly detection, and automated quality remediation are improving consistency while enabling organizations to process growing volumes of structured and unstructured data more efficiently.

"Data preparation has become a critical control point for enterprise AI," said Alexander Wurm, Principal Analyst at Nucleus Research. "Organizations realize ROI when trusted, governed data is available to analytics and AI systems without adding complexity to the preparation process."

Self-service capabilities continue to expand across the market. Natural language interfaces, visual workflow design, and AI-generated transformation logic are enabling analysts and business users to prepare data without extensive engineering support. This broader accessibility reduces dependence on technical teams while accelerating the delivery of insights across the enterprise.

Organizations are also placing greater emphasis on governed, AI-ready data. Semantic context, standardized definitions, lineage, and quality controls are becoming foundational requirements as AI agents and analytics platforms consume larger volumes of enterprise information. Vendors that combine automation, governance, and usability are helping customers improve productivity, shorten time to insight, and create a stronger foundation for scalable analytics and AI adoption.

Leaders in the Value Matrix excel in both functionality and usability, offering comprehensive solutions that deliver high ROI and support large-scale adoption. Leaders in this year's Value Matrix include Alteryx, Databricks, Dataiku, Domo, and ThoughtSpot.

Expert vendors offer deep, specialized functionality suited for complex requirements. These include Microsoft, Qlik, SAP, and SAS.

Accelerators focus on usability and ease of deployment, providing simpler solutions that enable quick adoption with less complexity. This year's Accelerators are AWS, Sigma, Tableau (Salesforce), and Zoho.

Core Providers offer essential, reliable functionalities, ideal for organizations with basic needs. This year's Core Providers are Altair (Siemens), Datameer, EasyMorph, and KNIME.

To download the 2026 Data Preparation Technology Value Matrix, click here.

About Nucleus Research

Nucleus Research is the recognized global leader in ROI technology research. Using a case-based approach, we provide research streams and advisory services that allow vendors and end users to quantify and maximize the return from their technology investments. For more information, visit NucleusResearch.com or follow our latest updates on LinkedIn.

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SOURCE Nucleus Research