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Governments can uncover very useful insights when data is shared across agencies. But this can be a difficult task. Hint: The challenge isn’t the tech. In this episode, we unpack some common data-sharing challenges and remedies. We also share two inspiring examples of how data sharing has improved government services.
Example 1: Virginia Vaccine Management and Allocation Exchange (VaxMaX) - Hear out data-sharing helped combat COVID-19.
Example 2: Utah’s Social Service Blueprint Solution - Utah was able to improve the effectiveness of five key social service programs by sharing data. There’s even a publicly available MOU for reference.
You might also like to hear the complete story of Utah’s Blueprint Solution in this video with Rachel Stone, Chief Data Officer from Utah GOPB, and Eric Clark from SpringML.
Some key considerations for your data sharing project:
1) Get started on MOU’s early and build clear support for the cause of data sharing
2) Use data classification smartly to build generalized MOUs to allow easier sharing of non-sensitive shareable data
3) Central IT should support the business needs and help pave the way for easier cross-agency data sharing with strong governance, data catalogs, and analytics technology that can be used across the state.
Governments can uncover very useful insights when data is shared across agencies. But this can be a difficult task. Hint: The challenge isn’t the tech. In this episode, we unpack some common data-sharing challenges and remedies. We also share two inspiring examples of how data sharing has improved government services.
Example 1: Virginia Vaccine Management and Allocation Exchange (VaxMaX) - Hear out data-sharing helped combat COVID-19.
Example 2: Utah’s Social Service Blueprint Solution - Utah was able to improve the effectiveness of five key social service programs by sharing data. There’s even a publicly available MOU for reference.
You might also like to hear the complete story of Utah’s Blueprint Solution in this video with Rachel Stone, Chief Data Officer from Utah GOPB, and Eric Clark from SpringML.
Some key considerations for your data sharing project:
1) Get started on MOU’s early and build clear support for the cause of data sharing
2) Use data classification smartly to build generalized MOUs to allow easier sharing of non-sensitive shareable data
3) Central IT should support the business needs and help pave the way for easier cross-agency data sharing with strong governance, data catalogs, and analytics technology that can be used across the state.