Modern data serialization formats: Parquet, Apache Arrow (Feather/IPC), Lance (ML-native), Zarr (chunked arrays), Avro, and ORC. Covers compression, partitioning, and format selection.
Quickly install data-engineering-storage-formats AI skill to your development environment via command line
Source: legout/data-platform-agent-skills.
Comprehensive guide to modern data serialization formats for analytics and machine learning: Parquet, Apache Arrow, Lance, Zarr, Avro, and ORC. Learn compression tradeoffs, partitioning strategies, and when to use each format.
| Format | Type | Best For | Compression | Schema Evolution | Random Access |
| Parquet | Columnar | Analytics, data lakes | ✅ (Snappy, Zstd, LZ4) | ✅ (add/drop) | ✅ (row groups) | | Arrow/Feather | Columnar | In-memory, IPC, ML | ✅ (LZ4, Zstd) | Limited | ✅ (record batches) | | Lance | Columnar | ML pipelines, vectors | ✅ (Zstd, LZ4) | ✅ | ✅ (multi-modal) |
Modern data serialization formats: Parquet, Apache Arrow (Feather/IPC), Lance (ML-native), Zarr (chunked arrays), Avro, and ORC. Covers compression, partitioning, and format selection. Source: legout/data-platform-agent-skills.
Stable fields and commands for AI/search citations.
npx skills add https://github.com/legout/data-platform-agent-skills --skill data-engineering-storage-formatsModern data serialization formats: Parquet, Apache Arrow (Feather/IPC), Lance (ML-native), Zarr (chunked arrays), Avro, and ORC. Covers compression, partitioning, and format selection. Source: legout/data-platform-agent-skills.
Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/legout/data-platform-agent-skills --skill data-engineering-storage-formats Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code, Cursor, or OpenClaw
https://github.com/legout/data-platform-agent-skills