Trending repositories for topic data-quality
The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
Learn how to design, develop, deploy and iterate on production-grade ML applications.
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
OpenMetadata is a unified metadata platform for data discovery, data observability, and data governance powered by a central metadata repository, in-depth column level lineage, and seamless team colla...
Always know what to expect from your data.
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
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.
:zap: Data quality testing for the modern data stack (SQL, Spark, and Pandas) https://www.soda.io
Possibly the fastest DataFrame-agnostic quality check library in town.
Feathr – A scalable, unified data and AI engineering platform for enterprise
lakeFS - Data version control for your data lake | Git for data
Possibly the fastest DataFrame-agnostic quality check library in town.
The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
OpenMetadata is a unified metadata platform for data discovery, data observability, and data governance powered by a central metadata repository, in-depth column level lineage, and seamless team colla...
:zap: Data quality testing for the modern data stack (SQL, Spark, and Pandas) https://www.soda.io
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.
A curated, but incomplete, list of data-centric AI resources.
Always know what to expect from your data.
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
Feathr – A scalable, unified data and AI engineering platform for enterprise
Learn how to design, develop, deploy and iterate on production-grade ML applications.
lakeFS - Data version control for your data lake | Git for data
The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
OpenMetadata is a unified metadata platform for data discovery, data observability, and data governance powered by a central metadata repository, in-depth column level lineage, and seamless team colla...
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
Learn how to design, develop, deploy and iterate on production-grade ML applications.
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.
Always know what to expect from your data.
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
:zap: Data quality testing for the modern data stack (SQL, Spark, and Pandas) https://www.soda.io
Learn how to design, develop, deploy and iterate on production-grade ML applications.
First open-source data discovery and observability platform. We make a life for data practitioners easy so you can focus on your business.
Home of the Open Data Contract Standard (ODCS).
📙 Awesome Data Catalogs and Observability Platforms.
Data quality assessment and metadata reporting for data frames and database tables
lakeFS - Data version control for your data lake | Git for data
Papers about training data quality management for ML models.
Papers about training data quality management for ML models.
DataOps Data Quality TestGen is part of DataKitchen's Open Source Data Observability. DataOps TestGen delivers simple, fast data quality test generation and execution by data profiling, new dataset...
The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
Home of the Open Data Contract Standard (ODCS).
pyDVL is a library of stable implementations of algorithms for data valuation and influence function computation
OpenMetadata is a unified metadata platform for data discovery, data observability, and data governance powered by a central metadata repository, in-depth column level lineage, and seamless team colla...
CSV Lint plug-in for Notepad++ for syntax highlighting, csv validation, automatic column and datatype detecting, fixed width datasets, change datetime format, decimal separator, sort data, count uniqu...
Possibly the fastest DataFrame-agnostic quality check library in town.
📙 Awesome Data Catalogs and Observability Platforms.
:zap: Data quality testing for the modern data stack (SQL, Spark, and Pandas) https://www.soda.io
First open-source data discovery and observability platform. We make a life for data practitioners easy so you can focus on your business.
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 quality assessment and metadata reporting for data frames and database tables
Learn how to design, develop, deploy and iterate on production-grade ML applications.
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 acr...
The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
OpenMetadata is a unified metadata platform for data discovery, data observability, and data governance powered by a central metadata repository, in-depth column level lineage, and seamless team colla...
Learn how to design, develop, deploy and iterate on production-grade ML applications.
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
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.
Always know what to expect from your data.
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
First open-source data discovery and observability platform. We make a life for data practitioners easy so you can focus on your business.
Learn how to design, develop, deploy and iterate on production-grade ML applications.
:zap: Data quality testing for the modern data stack (SQL, Spark, and Pandas) https://www.soda.io
Data quality assessment and metadata reporting for data frames and database tables
lakeFS - Data version control for your data lake | Git for data
📙 Awesome Data Catalogs and Observability Platforms.
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 collect...
Home of the Open Data Contract Standard (ODCS).
Papers about training data quality management for ML models.
Papers about training data quality management for ML models.
Scalable data pre processing and curation toolkit for LLMs
A curated list of awesome open source tools and commercial products for monitoring data quality, monitoring model performance, and profiling data 🚀
DataOps Data Quality TestGen is part of DataKitchen's Open Source Data Observability. DataOps TestGen delivers simple, fast data quality test generation and execution by data profiling, new dataset...
SparkConnect Server plugin and protobuf messages for the Amazon Deequ Data Quality Engine.
pyDVL is a library of stable implementations of algorithms for data valuation and influence function computation
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 f...
Home of the Open Data Contract Standard (ODCS).
OpenMetadata is a unified metadata platform for data discovery, data observability, and data governance powered by a central metadata repository, in-depth column level lineage, and seamless team colla...
Offical Repo for "Programming Every Example: Lifting Pre-training Data Quality Like Experts at Scale"
📙 Awesome Data Catalogs and Observability Platforms.
First open-source data discovery and observability platform. We make a life for data practitioners easy so you can focus on your business.
Data quality assessment and metadata reporting for data frames and database tables
The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
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 acr...
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.
:zap: Data quality testing for the modern data stack (SQL, Spark, and Pandas) https://www.soda.io
A tool to help improve data quality standards in observational data science.
A curated list of awesome resources such as books, tutorials, courses, open-source libraries, exercises, and other materials that support Pythonistas in the making, and Pythonistas migrating into Data...
Open-Source Software, Tutorials, and Research on Data-Centric AI 🤖
Offical Repo for "Programming Every Example: Lifting Pre-training Data Quality Like Experts at Scale"
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 acr...
三足乌数据中台融合数据规划、数据接入、数据开发、数据仓库、数据治理、数据资产、数据服务、数据运维、系统管理等功能模块为一体。打通数据壁垒，解决数据孤岛问题，实现数据的低代码可视化开发，助力政府、企业数字化转型。
DataOps Data Quality TestGen is part of DataKitchen's Open Source Data Observability. DataOps TestGen delivers simple, fast data quality test generation and execution by data profiling, new dataset...
Dataset Viber is your chill repo for data collection, annotation and vibe checks.
Papers about training data quality management for ML models.
A demo of Bufstream, a drop-in replacement for Apache Kafka that's 10x less expensive to operate
SparkConnect Server plugin and protobuf messages for the Amazon Deequ Data Quality Engine.
Learn how to design, develop, deploy and iterate on production-grade ML applications.
OpenMetadata is a unified metadata platform for data discovery, data observability, and data governance powered by a central metadata repository, in-depth column level lineage, and seamless team colla...
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
The standard data-centric AI package for data quality and machine learning with messy, real-world data and 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.
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
Always know what to expect from your data.
Scalable data pre processing and curation toolkit for LLMs
lakeFS - Data version control for your data lake | Git for data
Learn how to design, develop, deploy and iterate on production-grade ML applications.
:zap: Data quality testing for the modern data stack (SQL, Spark, and Pandas) https://www.soda.io
Home of the Open Data Contract Standard (ODCS).
📙 Awesome Data Catalogs and Observability Platforms.
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 collect...
First open-source data discovery and observability platform. We make a life for data practitioners easy so you can focus on your business.
Offical Repo for "Programming Every Example: Lifting Pre-training Data Quality Like Experts at Scale"
The Virtual Feature Store. Turn your existing data infrastructure into a feature store.
Scalable data pre processing and curation toolkit for LLMs
三足乌数据中台融合数据规划、数据接入、数据开发、数据仓库、数据治理、数据资产、数据服务、数据运维、系统管理等功能模块为一体。打通数据壁垒，解决数据孤岛问题，实现数据的低代码可视化开发，助力政府、企业数字化转型。
Home of the Open Data Contract Standard (ODCS).
This repository serves as a comprehensive guide to effective data modeling and robust data quality assurance using popular open-source tools
A demo of Bufstream, a drop-in replacement for Apache Kafka that's 10x less expensive to operate
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 f...
Possibly the fastest DataFrame-agnostic quality check library in town.
Intelligent Data Analysis (IAU_B) @ FIIT STU in Bratislava
pyDVL is a library of stable implementations of algorithms for data valuation and influence function computation
A curated list of awesome open source tools and commercial products for monitoring data quality, monitoring model performance, and profiling data 🚀
OpenMetadata is a unified metadata platform for data discovery, data observability, and data governance powered by a central metadata repository, in-depth column level lineage, and seamless team colla...
Free Open-source ML observability course for data scientists and ML engineers. Learn how to monitor and debug your ML models in production.
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 Prod...
📙 Awesome Data Catalogs and Observability Platforms.
CSV Lint plug-in for Notepad++ for syntax highlighting, csv validation, automatic column and datatype detecting, fixed width datasets, change datetime format, decimal separator, sort data, count uniqu...
A tool to help improve data quality standards in observational data science.
The standard data-centric AI package for data quality and machine learning with messy, real-world data and 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.