In the first article, I walked through a small Python data quality ETL starter that reads messy CSV,...
In the first article, I walked through a small Python data quality ETL starter that reads messy CSV, Excel, JSON, and API-style data, validates it, cleans it, exports it, and generates quality reports.
Previous article:
Build a Python Data Quality ETL Starter for Messy CSV, Excel, JSON, and API-Style Data
This follow-up focuses on the v0.4.0 update of the same project:
Data Quality ETL Starter on GitHub
The best way to actually understand data engineering is to build something that breaks, fix it, and...
I published a public data engineering project that demonstrates a cloud-based ETL pipeline for...
I rebuilt the core ideas behind Parquet — encodings, compression, row groups, projection & predicate pushdown — in ~3,000 lines…
Most Python tutorials teach you to write Python. This one teaches you to write pipelines. The code...
TL;DR In Part 1, Athena provided serverless read-only SQL. In Part 2, Databricks hit...
Hey everyone, I wanted to share NexusOS v2.0, a self-hosted data factory project I've been working...
