#Dataquality
Showing 17 of 17 repositories tagged #dataquality, ranked by stars
Always know what to expect from your data.
Compare tables within or across databases
Data Contracts engine for the modern data stack. https://www.soda.io
re_data - fix data issues before your users & CEO would discover them 😊
Scalable master data management, identity resolution, entity resolution, and deduplication using ML
ML powered analytics engine for outlier detection and root cause analysis.
Know your data better！Datavines is Next-gen Data Observability Platform, support metadata manage and data quality.
Dingo: A Comprehensive AI Data, Model and Application Quality Evaluation Tool
The premier open source Data Quality solution
Library for Semi-Automated Data Science
Possibly the fastest DataFrame-agnostic quality check library in town.
Open Source Data Quality Monitoring.
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.
Find data quality issues and clean your data in a single line of code with a Scikit-Learn compatible Transformer.
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 hygiene review, AI generation of data quality validation tests, ongoing testing of data refreshes, & continuous anomaly monitoring
:zap: Prevent downstream data quality issues by integrating the Soda Library into your CI/CD pipeline.
Huemul BigDataGovernance, es una framework que trabaja sobre Spark, Hive y HDFS. Permite la implementación de una estrategia corporativa de dato único, basada en buenas prácticas de Gobierno de Datos. Permite implementar tablas con control de Primary Key y Foreing Key al insertar y actualizar datos utilizando la librería, Validación de nulos, largos de textos, máximos/mínimos de números y fechas, valores únicos y valores por default. También permite clasificar los campos en aplicabilidad de derechos ARCO para facilitar la implementación de leyes de protección de datos tipo GDPR, identificar los niveles de seguridad y si se está aplicando algún tipo de encriptación. Adicionalmente permite agregar reglas de validación más complejas sobre la misma tabla.