# 10-05-2023 From Feature Engineering to Data Storage ## This week you will... * learn about meta data from a machine learning pipe line * learn about managing evolving data * get an overview on enterprise storage solutions ## Learning Resources * [Machine Learning Data Lifecycle in Production](https://www.coursera.org/learn/machine-learning-data-lifecycle-in-production/home/week/2): Week 2 and Week 3 ## Until next week you should.. * complete week 4 of the course [Machine Learning Data Lifecycle in Production](https://www.coursera.org/learn/machine-learning-data-lifecycle-in-production/home/week/4) and week 1 of the course [Machine Learning Modeling Pipelines in Production](https://www.coursera.org/learn/machine-learning-modeling-pipelines-in-production/home/week/1); including the provided exercises/labs. --- # 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://opencampus.gitbook.io/opencampus-machine-learning-program/courses/archive/machine-learning-operations-mlops/10-05-2023-from-feature-engineering-to-data-storage.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.