great-expectations / great_expectations
Always know what to expect from your data.
☆10,386Updated this week
Alternatives and similar repositories for great_expectations
Users that are interested in great_expectations are comparing it to the libraries listed below
Sorting:
- Deequ is a library built on top of Apache Spark for defining "unit tests for data", which measure data quality in large datasets.☆3,415Updated 3 weeks ago
- Data quality testing for the modern data stack (SQL, Spark, and Pandas) https://www.soda.io☆2,085Updated this week
- Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and…☆10,337Updated this week
- Amundsen is a metadata driven application for improving the productivity of data analysts, data scientists and engineers when interacting…☆4,569Updated 3 weeks ago
- A light-weight, flexible, and expressive statistical data testing library☆3,807Updated this week
- The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️☆3,571Updated 7 months ago
- 🦉 Data Versioning and ML Experiments☆14,462Updated this week
- Build, Manage and Deploy AI/ML Systems☆8,807Updated this week
- ♾️ CML - Continuous Machine Learning | CI/CD for ML☆4,100Updated this week
- dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build application…☆10,827Updated this week
- ZenML 🙏: The bridge between ML and Ops. https://zenml.io.☆4,581Updated this week
- A unified interface for distributed computing. Fugue executes SQL, Python, Pandas, and Polars code on Spark, Dask and Ray without any rew…☆2,081Updated last month
- The Open Source Feature Store for AI/ML☆6,056Updated this week
- An open-source data logging library for machine learning models and data pipelines. 📚 Provides visibility into data quality & model perf…☆2,715Updated 4 months ago
- Evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. Fro…☆6,149Updated this week
- re_data - fix data issues before your users & CEO would discover them 😊☆1,562Updated last year
- Curated list of resources about Apache Airflow☆3,779Updated 8 months ago
- Scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks.☆6,237Updated this week
- Prefect is a workflow orchestration framework for building resilient data pipelines in Python.☆19,290Updated this week
- An orchestration platform for the development, production, and observation of data assets.☆13,121Updated this week
- 1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.☆12,907Updated this week
- Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metada…☆2,130Updated this week
- Scalable and efficient data transformation framework - backwards compatible with dbt.☆2,301Updated this week
- Python API for Deequ☆768Updated last month
- An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models☆4,523Updated this week
- Apache Airflow - A platform to programmatically author, schedule, and monitor workflows☆40,052Updated this week
- A curated list of awesome pipeline toolkits inspired by Awesome Sysadmin☆6,363Updated 2 months ago
- Meltano: the declarative code-first data integration engine that powers your wildest data and ML-powered product ideas. Say goodbye to wr…☆2,057Updated this week
- A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.☆8,901Updated last week
- Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization and exploration of big tabular data at a billion rows per s…☆8,381Updated 7 months ago