Government &
Education Data Cloud
Data-driven decision-making for the public sector.
Share and collaborate with data, eliminate fraud, waste and abuse, and gain a holistic view
Snowflake's Government & Education Data Cloud enables data sharing, collaboration, and informed decision-making in the public sector. Organizations can modernize and accelerate cloud migration, as well as collaborate and share data within and across agencies and departments. It also provides public sector leaders with holistic views of citizens, students, and patients and helps prevent and protect against fraud, waste, and abuse.
Solutions in the
Government & Education Data Cloud
SHARE AND COLLABORATE WITH DATA
A single, integrated, and cross-cloud data platform eliminates technical and institutional data silos and ensures high levels of data security and governance in accordance with government authorizations. Support for regulated customer workloads allows organizations to securely share data across teams, between agencies, and externally with the public or the private sector.
GAIN 360° VIEWS OF STAKEHOLDERS
Governments and education institutions can combine data sources to create holistic 360-degree views of entities, citizens, recipients, and students. Centralizing stakeholder data helps leaders make data-driven decisions and deliver better services.
MONITOR FOR FRAUD, WASTE, & ABUSE
Public sector organizations can detect and prevent fraud sooner by addressing their technology and data limitations. With a single source of truth, advanced analytics capabilities, and AI and machine learning, organizations can track and respond quickly to improper payments, flag fraudulent claims and applications, and reduce waste wherever payments occur.
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Modernizing Data Management In State Government With Texas Health & Human Services
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Try Snowflake free for 30 days and experience the Data Cloud that helps eliminate the complexity, cost, and constraints inherent with other solutions. Available on all three major clouds, Snowflake supports a wide range of workloads, such as data warehousing, data lakes, AI and machine learning.