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Ready to dive into the world of data lakes and supercharge your analytics? But first, let's address the elephant in the room: CSV files. Sure, CSV files have been hanging around like that old sweater in your closet, but when it comes to storing data in a data lake for analytical purposes, they're about as effective as using a toothpick to carve a Thanksgiving turkey! Enter Parquet - the data lake's best friend! Want to know all the juicy details about why Parquet is your data lake's new BFF? Join me in my video where I'll spill all the secrets and show you how to harness the power of Parquet for your analytical needs. Get ready to transform your data lake experience – it's going to be epic! ▬▬▬▬▬▬ IMPORTANT LINKS ▬▬▬▬▬▬ My LinkedIn profile: / piotr-tybulewicz-81a8793 GitHub with my drawings: https://github.com/TybulOnAzure/DP-203 Parquet Viewer: https://github.com/mukunku/ParquetViewer ▬▬▬▬▬▬ SUPPORTING MY CHANNEL ▬▬▬▬▬▬ Buy me a coffee (or beer): https://buymeacoffee.com/piotrv Join this channel to get access to perks: / @tybulonazure ▬▬▬▬▬▬ CHAPTERS ▬▬▬▬▬▬ 00:00 Introduction 00:31 Parquet overview 03:31 ParquetViewer 07:33 Storage modes 15:21 Row storage 18:38 Columnar storage 24:17 Hybrid storage 32:16 Compression 39:36 Schema 42:57 Summary