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On the policy front, a feature like Policy Center empowers users to enforce and track policies at scale; this ensures that people use data compliantly, and organizations are prepared for compliance audits. For instance, technical power users can explore the actual data through Compose , the intelligent SQL editor. Spoiler alert!
Building data pipelines is challenging, and complex requirements (as well as the separation of many sources) leads to a lack of trust. Troubleshooting data issues , for an exploding number of disjointed systems and tools, breaks self-service for data users and creates gaps in visibility for dataOps.
There are many frameworks for testing software, but the right way to test the data and SQL scripts that change data are less obvious. This is because databases and the data therein are constantly changing. To truly test the effects of a deployment, you need to have an environment with the exact data that is in Production.
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