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Articles tagged with #data-engineering
Up to this point in my data engineering project, I had already worked with the individual parts of a modern data stack: dlt for ingestion, Snowflake for storage, dbt for transformation, and dbt tests
This blog walks through the full lifecycle of a modern data warehouse, from setting up Snowflake infrastructure and access control to ingesting API data with dlt, transforming it with dbt, modeling it
Principles of Good Data Engineering One major challenge is the ambiguity in metrics and the ambiguity in human questions. For data to deliver meaningful answers, the underlying data must be supported
I built an ETL pipeline that takes messy product data from a CSV file, cleans and validates it, and loads both trusted and rejected records into PostgreSQL. https://github.com/Akina-Aoki/data_ops_work
Product Finder is a retail data platform prototype built for SportsWear AB. The goal is simple: take inventory and sales events from operations, process them in a reliable pipeline, and turn them into
Project Summary This project explores the Sakila DVD rental database using SQL, DuckDB, Python, and Evidence. The goal is to understand the data and find patterns in movies, customers, and revenue. The data is loaded from a SQLite database into DuckD...
