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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May 31, 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.
Data quality checks to curate noisy labels in the data
Source-available data quality tool
⚡ Data quality testing for the modern data stack (SQL, Spark, and Pandas) https://www.soda.io
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.
Possibly the fastest DataFrame-agnostic quality check library in town.
数据质量检查工具, 用于诊断数据的问题
A library for authoring DLT pipelines via meta-programming patterns and deploying to Databricks workspaces.
Engine for ML/Data tracking, visualization, explainability, drift detection, and dashboards for Polyaxon.
Data Quality Monitor (DQM) - Continuously validate your data with easy, customizable rules.
re_data - fix data issues before your users & CEO would discover them 😊
collection of Jupyter Notebooks in both English and Spanish, dedicated to performing data quality analysis using the R programming language
Swiple enables you to easily observe, understand, validate and improve the quality of your data
Collection of R scripts to test packages in conducting data quality assessments
Safety net for machine learning pipelines. Plays nice with sklearn and pandas.
A Stata template for running high frequency checks of incoming research data at Innovations for Poverty Action
Data quality monitoring library designed for time series data, made for modern data stack
Real-time streaming data quality validation project using NYC Taxi Rides datasets, leveraging Kafka, Flink, and StreamDQ.
hooqu is a library built on top of Pandas-like Dataframes for defining "unit tests for data". This is a spiritual port of Apache Deequ to Python
Backend de dataguadian Pro : plateforme de profilage et correction de base de données
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