The Open Context Layer for Data and AI , OpenMetadata is the open platform for building trusted data context and business semantics for humans, AI assistants, and agents.
- metadata
- datadiscovery
- dataquality
- data-profiling
Repository Index
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1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
- pandas-profiling
- pandas-dataframe
- statistics
- jupyter-notebook
Always know what to expect from your data.
- pipeline-tests
- dataquality
- datacleaning
- datacleaner
Cleanlab's open-source library is the standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
- weak-supervision
- data-cleaning
- data-quality
- noisy-labels
Evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.
- data-drift
- jupyter-notebook
- pandas-dataframe
- machine-learning
Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.
- machine-learning
- ml
- model-validation
- data-validation
An open-source data logging library for machine learning models and data pipelines. 📚 Provides visibility into data quality & model performance over time. 🛡️ Supports privacy-preserving data collection, ensuring safety & robustness. 📈
- ai-pipelines
- approximate-statistics
- statistical-properties
- data-quality
Data Contracts engine for the modern data stack. https://www.soda.io
- python
- data-engineering
- data-governance
- data-monitoring
The dbt-native data observability solution for data & analytics engineers. Monitor your data pipelines in minutes. Available as self-hosted or cloud service with premium features.
- data-lineage
- data-governance
- data-warehouse
- snowflake
Open-source low code data preparation library in python. Collect, clean and visualization your data in python with a few lines of code.
- dataprep
- data-science
- datapreparation
- dataconnector
Build data pipelines with SQL and Python, ingest data from different sources, add quality checks, and build end-to-end flows.
- analytics
- bigquery
- data-modeling
- data-pipelines
Library for exploring and validating machine learning data
pyspark methods to enhance developer productivity 📣 👯 🎉
Pandas, Polars, Spark, and Snowpark DataFrame comparison for humans and more!
Utility to compare data between homogeneous or heterogeneous environments to ensure source and target tables match
Desbordante is a high-performance data profiler that is capable of discovering many different patterns in data using various algorithms. It also allows to run data cleaning scenarios using these algorithms. Desbordante has a console version and an easy-to-use web application.
- data-analytics
- data-cleaning
- data-cleansing
- data-engineering
The repository host gives no description.
- hacktoberfest
- data
- datalineage
- dbt
Data Quality and Observability platform for the whole data lifecycle, from profiling new data sources to full automation with Data Observability. Configure data quality checks from the UI or in YAML files, let DQOps run the data quality checks daily to detect data quality issues.
- data-ops
- data-quality
- data-quality-checks
- data-quality-measurement
Generate the smallest test dataset that provably catches broken data-mapping rules in ETL pipelines.
Field-level assurance for data pipelines: mapping-driven source-to-target validation, fault-injection test scoring and explainable risk-adaptive test prioritization.
Declarative data quality engine. Define checks in YAML, run anywhere.
- airflow
- anomaly-detection
- data-contracts
- data-quality
A detective for your data. Zero-config data quality monitoring — works with dbt, Postgres, BigQuery, Snowflake. No YAML.
- anomaly-detection
- bigquery
- cli
- data-engineering
Blazingly fast data comparison tool for Python, powered by Rust. Compare massive CSV/Parquet datasets instantly.
Validates tabular CSV data using predefined validations, inspired from its Python homologue "Great Expectations".
- common-lisp
- csv
- data-validation
- great-expectations