Data modernization efforts are driving a culture shift that impacts how systems, data, processes, and workforce operate across the public health ecosystem. At the national level, federal funders are working to align their programmatic funding requirements with broader national data modernization goals. To learn more about data modernization at the national level, visit the “What is the Data Modernization Initiative?” section of the toolkit. 

Public health agencies are taking strategic approaches to break down silos and share data across programs and with the public. As a part of this work, agencies are establishing enterprise data platforms (also called data lakes, data warehouses or data lakehouses) to provide a centralized source of data. Data modernization teams are requesting participation from programs and systems, like immunization, to contribute data to these platforms, and that comes with opportunities and concerns. These platforms have the potential to provide a bigger picture and gain insights from across multiple data sources, such as overlaying vaccination records with disease outbreaks to better target resources and public health interventions. When epidemiologists and informaticians have access to consolidated and validated datasets, it helps assure teams do not generate conflicting calculations or metrics. The resulting data can be used with confidence to develop dynamic, public-facing dashboards, increasing transparency and building trust with constituents. To learn more about enterprise data platforms, visit the “Technology development and acquisition” section of the toolkit.

The increase of data flowing from multiple programs into a single repository has the potential for a loss of connection to the data’s original source thus isolating the data from its context, preventing context-based decision-making, and opening the data to misuse. This is a valid concern for immunization and many other programs across public health agencies. Programs are the stewards of their data, and it is their responsibility to verify its appropriate use. Programmatic data shared with enterprise data platforms need to retain their programmatic protections and be used in adherence with the laws and regulations specific to that particular dataset, and their respective data use agreements. Strong metadata and governance practices are essential to maintain a linkage to the original data source and provide clear, consistent rules for how each dataset will be stored, used, protected and shared in an enterprise data platform. To learn more about metadata and data governance in public health, visit the “Assess governance and policy” section of the toolkit.