Data Wrangling: Key Concepts for Preparing Data in ML Pipelines

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Duration: 19:30
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This stream covers core concepts around data wrangling including ETL vs ELT data pipelines, the iterative process of data discovery, structuring, cleaning, enriching, validating and publishing data. It compares traditional ETL flows for structured data vs ELT flows better suited for large volumes of raw, unstructured data destined for data lakes.\n\n\nHey readers πŸ‘‹, if you enjoyed this content, I wanted to share some of my favorite resources to continue your learning journey in technology!\nHands-On Courses for Rust, Data, Cloud, AI and LLMs πŸš€\n\nRust Programming Specialization: https://insight.paiml.com/qwh\nRust for DevOps: https://insight.paiml.com/x14\nRust LLMOps: https://insight.paiml.com/g3b\nRust Fundamentals: https://insight.paiml.com/qyt\nData Engineering with Rust: https://insight.paiml.com/zm1\nPython and Rust with Linux Command Line Tools: https://insight.paiml.com/jot