Open Standard for Metadata. A Single place to Discover, Collaborate and Get your data right.
-
Updated
Apr 28, 2024 - TypeScript
Open Standard for Metadata. A Single place to Discover, Collaborate and Get your data right.
⚡ Data quality testing for the modern data stack (SQL, Spark, and Pandas) https://www.soda.io
re_data - fix data issues before your users & CEO would discover them 😊
Engine for ML/Data tracking, visualization, explainability, drift detection, and dashboards for Polyaxon.
🐳 Tool to automate data quality checks on data pipelines
数据治理、数据质量检核/监控平台(Django+jQuery+MySQL)
An RDF Unit Testing Suite
Possibly the fastest DataFrame-agnostic quality check library in town.
NBi is a testing framework (add-on to NUnit) for Business Intelligence and Data Access. The main goal of this framework is to let users create tests with a declarative approach based on an Xml syntax. By the means of NBi, you don't need to develop C# or Java code to specify your tests! Either, you don't need Visual Studio or Eclipse to compile y…
Swiple enables you to easily observe, understand, validate and improve the quality of your data
A Stata template for running high frequency checks of incoming research data at Innovations for Poverty Action
Lightweight library to write, orchestrate and test your SQL ETL. Writing ETL with data integrity in mind.
Free Open-source ML observability course for data scientists and ML engineers. Learn how to monitor and debug your ML models in production.
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 Quality Monitor (DQM) - Continuously validate your data with easy, customizable rules.
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
The PEDSnet Data Quality Assessment Toolkit (OMOP CDM)
Safety net for machine learning pipelines. Plays nice with sklearn and pandas.
🔍Your Data Quality Detector / Gain insight into your data and get it ready for use before you start working with it 💡📊🛠💎
⚡ Prevent downstream data quality issues by integrating the Soda Library into your CI/CD pipeline.
Add a description, image, and links to the data-quality-checks topic page so that developers can more easily learn about it.
To associate your repository with the data-quality-checks topic, visit your repo's landing page and select "manage topics."