Summary
This document is a checklist designed to ensure data readiness for artificial intelligence (AI) applications. It outlines six essential steps that organizations should follow to prepare their data for AI use cases effectively. The checklist emphasizes the importance of aligning stakeholders with a data readiness strategy, defining and supporting data quality standards, managing data quality as a lifecycle, creating a balanced strategy tailored to specific business needs, leveraging data intelligence to support AI, and ensuring modern data observability capabilities are in place. Each step includes critical questions that teams must address to mitigate risks and enhance data quality. The document highlights the necessity of collaboration among various roles, including business users, data stewards, IT developers, and data scientists, to ensure that data meets technical and compliance requirements. By following this checklist, organizations can optimize their data management practices and improve the success rate of their AI initiatives.
