# Overview {% embed url="" %} Overview - Data Management {% endembed %} ## Summary * Data science has never been as much about machine learning as it has about cleaning, shaping, and moving data from place to place. * Here are the important concepts in data management: * **Sources -** how to get training data * **Labeling -** how to label proprietary data at scale * **Storage -** how to store data and metadata appropriately * **Versioning -** how to update data through user activity or additional labeling * **Processing -** how to aggregate and convert raw data and metadata --- # 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://fall2019.fullstackdeeplearning.com/course-content/data-management/overview.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.