# Use cases ## Contents ### Data Compliance for Data Scientists Develop ML-models meeting compliance standards and make sure that you manage Personally Identifiable Information (PII) properly. [Read more](/use_cases/dc_data_compliance.md) ### Deprecation for Data Engineer \ Analyst 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. [Read more](/use_cases/de_deprecation.md) ### Data quality and visibility for Quality Engineer 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. [Read more](/use_cases/dq_visibility.md) ### Data preparation for Viz Engineer 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. [Read more](/use_cases/viz_preparation.md) ### Service Provider and Pre-Sales Manage customer expectations successfully by examining an existing architectural landscape and gathering info about a toolset for better project scope planning. [Read more](/use_cases/service_presales.md) ### Newcomer onboarding Gather information about your data sources and owners, metadata description and lineage diagram in one place, so that a newcomer gets down to real tasks faster. ### Customer churn analysis for Data Scientist An imperfect notification system in your streaming pipeline may cause a problem when a training model receives irrelevant data. This use case shows how to launch enriched notifications provided by ODD & Open Telemetry integration. ### Recommendation engine with observable and manageable pipelines Build training models for your recommendation system without failures and obsolete data. This use case is about how ODD's alerts and end-to-end lineage helps avoid asynchronous run schedules of a model and an Airflow pipeline. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.opendatadiscovery.org/use_cases.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.