#Great-expectations
Showing 8 of 8 repositories tagged #great-expectations, ranked by stars
๐ ๐ง๐ต๐ฒ ๐๐๐น๐น ๐ฆ๐๐ฎ๐ฐ๐ธ ๐ณ-๐ฆ๐๐ฒ๐ฝ๐ ๐ ๐๐ข๐ฝ๐ ๐๐ฟ๐ฎ๐บ๐ฒ๐๐ผ๐ฟ๐ธ | ๐๐ฒ๐ฎ๐ฟ๐ป ๐ ๐๐ & ๐ ๐๐ข๐ฝ๐ for free by designing, building and deploying an end-to-end ML batch system ~ ๐ด๐ฐ๐ถ๐ณ๐ค๐ฆ ๐ค๐ฐ๐ฅ๐ฆ + 2.5 ๐ฉ๐ฐ๐ถ๐ณ๐ด ๐ฐ๐ง ๐ณ๐ฆ๐ข๐ฅ๐ช๐ฏ๐จ & ๐ท๐ช๐ฅ๐ฆ๐ฐ ๐ฎ๐ข๐ต๐ฆ๐ณ๐ช๐ข๐ญ๐ด
The Lakehouse Engine is a configuration driven Spark framework, written in Python, serving as a scalable and distributed engine for several lakehouse algorithms, data flows and utilities for Data Products.
Sample project to demonstrate data engineering best practices
๐ A scalable, production-ready data pipeline for real-time streaming & batch processing, integrating Kafka, Spark, Airflow, AWS, Kubernetes, and MLflow. Supports end-to-end data ingestion, transformation, storage, monitoring, and AI/ML serving with CI/CD automation using Terraform & GitHub Actions.
Learn how to create reliable ML systems by testing code, data and models.
Data Quality Gate based on AWS
ELT Data Pipeline implementation in Data Warehousing environment
A project for exploring how Great Expectations can be used to ensure data quality and validate batches within a data pipeline defined in Airflow.