1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.

Always know what to expect from your data.

The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

Visualize and compare datasets, target values and associations, with one line of code.

⚡ Data quality testing for the modern data stack (SQL, Spark, and Pandas) https://www.soda.io

🚚 Agile Data Preparation Workflows made easy with Pandas, Dask, cuDF, Dask-cuDF, Vaex and PySpark

Automatically find issues in image datasets and practice data-centric computer vision.

Engine for ML/Data tracking, visualization, explainability, drift detection, and dashboards for Polyaxon.

Monitor the stability of a Pandas or Spark dataframe ⚙︎

Code review for data in dbt

Lineage metadata API, artifacts streams, sandbox, API, and spaces for Polyaxon

Swiple enables you to easily observe, understand, validate and improve the quality of your data

a set of scripts to pull meta data and data profiling metrics from relational database systems

Installer for DataKitchen's Open Source Data Observability Products. Data breaks. Servers break. Your toolchain breaks. Ensure your team is the first to know and the first to solve with visibility across and down your data estate. Save time with simple, fast data quality test generation and execution. Trust your data, tools, and systems end to end.

Open-source metadata collector based on ODD Specification

Dataset search engine, discovering data from a variety of sources, profiling it, and allowing advanced queries on the index

Metadata and data identification tool and Python library. Identifies PII, common identifiers, language specific identifiers. Fully customizable and flexible rules

Client interface for all things Cleanlab Studio

A project for exploring how Great Expectations can be used to ensure data quality and validate batches within a data pipeline defined in Airflow.

Drift detection module for machine learning pipelines.