Introduction to Data Engineering Concepts | Data Quality and Validation
Explores the importance of data quality and validation in data engineering, covering key dimensions and tools for reliable pipelines.
Explores the importance of data quality and validation in data engineering, covering key dimensions and tools for reliable pipelines.
Notes on dataset engineering from Chip Huyen's 'AI Engineering', covering data curation, quality, coverage, quantity, and acquisition for AI models.
An introduction to Great Expectations, an open-source Python tool for data quality testing, documentation, and profiling.
Adding a PDF course completion report for students in a SaaS application built with Python and Django.