OpenMetadata is a unified platform for discovery, observability, and governance powered by a central metadata repository, in-depth lineage, and seamless team collaboration.
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Updated
May 28, 2024 - TypeScript
OpenMetadata is a unified platform for discovery, observability, and governance powered by a central metadata repository, in-depth lineage, and seamless team collaboration.
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.
Always know what to expect from your data.
Lineage metadata API, artifacts streams, sandbox, API, and spaces for Polyaxon
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.
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 testing for the modern data stack (SQL, Spark, and Pandas) https://www.soda.io
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.
The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
Open Standard for Metadata. A Single place to Discover, Collaborate and Get your data right.
Data preparation and exploration scripts
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
Client interface for all things Cleanlab Studio
Papers about training data quality management for ML models.
Metadata/data identification Java library. Identifies Semantic Type information (e.g. Gender, Age, Color, Country,...). Extensive country/language support. Extensible via user-defined plugins. Comprehensive Profiling support.
🚚 Agile Data Preparation Workflows made easy with Pandas, Dask, cuDF, Dask-cuDF, Vaex and PySpark
Engine for ML/Data tracking, visualization, explainability, drift detection, and dashboards for Polyaxon.
HPCC Systems ECL bundle that provides some basic data profiling and research tools to an ECL programmer
Swiple enables you to easily observe, understand, validate and improve the quality of your data
Automatically find issues in image datasets and practice data-centric computer vision.
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