great-expectations / great_expectations_actionLinks
A GitHub Action that makes it easy to use Great Expectations to validate your data pipelines in your CI workflows.
☆80Updated last year
Alternatives and similar repositories for great_expectations_action
Users that are interested in great_expectations_action are comparing it to the libraries listed below
Sorting:
- The easiest way to integrate Kedro and Great Expectations☆52Updated 2 years ago
- Supporting materials/code examples for my course in data engineering for machine learning.☆38Updated 2 years ago
- Great Expectations Airflow operator☆167Updated last week
- Build and deploy a serverless data pipeline on AWS with no effort.☆110Updated 2 years ago
- Fake Pandas / PySpark DataFrame creator☆47Updated last year
- Parse dbt artifacts and search dbt models with Algolia☆52Updated 4 years ago
- Code examples showing flow deployment to various types of infrastructure☆107Updated 2 years ago
- Tutorials for Fugue - A unified interface for distributed computing. Fugue executes SQL, Python, and Pandas code on Spark and Dask withou…☆113Updated last year
- Sample configuration to deploy a modern data platform.☆88Updated 3 years ago
- Learn how to add data validation and documentation to a data pipeline built with dbt and Airflow.☆169Updated last year
- Examples of various flow deployments for Prefect 1.0 (storage and run configurations)☆35Updated 3 years ago
- Ingesting data with Pulumi, AWS lambdas and Snowflake in a scalable, fully replayable manner☆71Updated 3 years ago
- Data-aware orchestration with dagster, dbt, and airbyte☆30Updated 2 years ago
- Templates for your Kedro projects.☆76Updated this week
- Possibly the fastest DataFrame-agnostic quality check library in town.☆195Updated last week
- Build your feature store with macros right within your dbt repository☆39Updated 2 years ago
- Capture all information throughout your model's development in a reproducible way and tie results directly to the model code!☆133Updated this week
- A tool to deploy a mostly serverless MLflow tracking server on a GCP project with one command☆70Updated 2 months ago
- Palm CLI - the tool-belt for data teams☆47Updated last year
- Dask integration for Snowflake☆30Updated 8 months ago
- Deploy production-grade Metaflow cloud infrastructure on AWS☆66Updated 2 months ago
- Pandas helper functions☆31Updated 2 years ago
- A dbt-Core package for generating models from an activity stream.☆43Updated last year
- Kedro Plugin to support running workflows on Kubeflow Pipelines☆54Updated 2 weeks ago
- Pipeline definitions for managing data flows to power analytics at MIT Open Learning☆43Updated this week
- A simple and easy to use Data Quality (DQ) tool built with Python.☆50Updated last year
- Experimental MLflow plugin for Google Cloud Vertex AI☆38Updated last month
- IbisML is a library for building scalable ML pipelines using Ibis.☆110Updated 6 months ago
- Repo for orienting dbt users to the Dagster asset framework☆54Updated 2 years ago
- A PyTest plugin to speed up your tests which depend on Snowflake sessions☆27Updated last month