Develop ML-models meeting compliance standards and make sure that you manage Personally Identifiable Information (PII) properly. See the Data compliance for Data Scientists use case for the end-to-end walkthrough.
Be in control of making dramatic changes to your data. Provide transparent deprecation process so as to inform all stakeholders in proper time and manage risks of downstream failure. See the Deprecation for Data Engineer / Analyst use case.
Import test suite results from pre-defined libraries or custom frameworks directly to the ODD Platform and share them with your team and other stakeholders to build trustworthy and transparent communication about data health of your product. See the Visibility for Data Quality Engineer use case.
There are numerous BI tools and their data preparation capabilities vary. Examine your data sources, metadata and tags using the ODD Platform to predict BI tool performance, set dashboard security levels and prepare the data. See the Data preparation for Visualization Engineer use case.
Manage customer expectations successfully by examining an existing architectural landscape and gathering info about a toolset for better project scope planning. See the Service Provider and Pre-Sales use case.
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