Transforming data chaos into clarity: Implementing a scalable data intelligence platform.

68 Background: City of Hope is dedicated to cancer research and treatment across multiple distinct geographic regions. Focusing on delivering top-tier clinical care, while providing research-based innovation, has resulted in a complex data architecture structure. Data management was becoming untenable, with no existing insight into where data was, how much overlapped, what was accurate, and what was being used. A data management and cataloging system was implemented to expose data, key attributes, and functions. 8 million unique assets have been located and are in process of curation for an effective repository of key information. Methods: Leveraging IT’s architecture teams, a tool search was completed choosing a data intelligence platform as the best match and value. The organization’s Data Governance infrastructure was employed to curate scanned metadata into domains and populate key information leveraging subject matter expert teams. Curation efforts focused on high-use data to provide accurate titles, definitions, and quality endorsements. Self-lead curation continues post-sprint for ongoing maintenance. Additional functions were utilized to create a repository of terms, definitions, and documentation. Results: 7,900,179 Catalog objects located, 240 Data Sources scanned, 426 users onboarded, 14% of data objects curated to date. The pilot showed 20 users achieved savings of $214K annually in wasted FTE time, with 100+ users estimated to save $1M in a year. The Quality team developed a user-friendly, centralized metric glossary of 161 metrics accessible for all, giving leaders and frontline teams a single source of truth for critical definitions and metrics. Conclusions: Curating assets and documenting tribal knowledge in a searchable platform gains a comprehensive view of those assets, making them easily discoverable, understandable, and accessible to all users, regardless of technical expertise. This achieves better decision-making, improved data quality, and efficient collaboration across the organization.