Analyst Report
In today's rapidly evolving AI landscape, ensuring your data is AI-ready is paramount. Organizations that fail to adapt to AI-specific data requirements risk falling behind. The Gartner latest research, "Quick Answer: What Makes Data AI-Ready?" provides invaluable insights and frameworks for data and analytics leaders to navigate this complex terrain.
Our key takeaways from the report:
Defining AI-Ready Data:
Understand the contextual requirements of your AI use cases.
Learn how data fitness varies depending on specific AI techniques.
Aligning Data with Use-Case Requirements:
Align your data with AI techniques and quantification needs.
Ensure data meets the expectations of diverse AI use cases.
Qualifying Data for AI:
Enrich data through semantics, annotation, and labeling.
Meet AI confidence requirements through data quality, trust, and diversity.
Governance and Compliance:
Implement continuous regression testing and observability metrics.
Adhere to AI ethics, data standards, and regulatory compliance.
Why we feel you must read this report:
Stay Ahead of the Curve: Equip your organization with the knowledge to meet the dynamic demands of AI technology.
Prove Data Readiness: Learn how to continuously qualify and govern your data for AI applications.
Optimize AI Implementation: Avoid common pitfalls and leverage best practices to maximize the success of your AI initiatives.
GartnerⓇ, Quick Answer: What Makes Data AI-Ready?, 15 May 2024, By Roxane Edjlali, Mark Beyer, Svetlana Sicular, Ehtisham Zaidi. GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved. Gartner does not endorse any vendor, product or service depicted in its research publications and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s Research & Advisory organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
Datasheet
Alation Data Quality leverages agentic AI and existing data intelligence to establish AI-recommended data quality rules and gauge overall data health across an entire data estate. Offering immediate visibility into the health of an organization’s most critical data assets, data consumers have access to data they can trust is accurate, up-to-date, and fit-for-purpose.
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