Data file examples and user guides for VerityPy and VerityDotNet libraries

Agentic Data Engineering Platform is an open-source, production-ready ETL solution that combines the Medallion Architecture with AI-powered agents that autonomously profile, clean, and optimize your data—so you can focus on insights, not infrastructure.

This GitHub repository provides a comprehensive set of tools and algorithms for detecting fraud anomalies in various data sources. Fraudulent activities can have severe consequences, impacting businesses and individuals alike. With this repository, we aim to empower researchers with effective techniques to identify and prevent fraudulent behavior.

Detecting errors and anomalies in structured data using automation

End-to-End Data Engineering Pipeline for E-commerce Analytics.

To describe age-gender unbiased COVID-19 subphenotypes regarding severity patterns through a two-stage clustering approach using patient phenotypes and demographic features. Additional source and temporal variability assessments are included as part of data quality analyses.

Data Trust Engineering (DTE) is a vendor-neutral, engineering-first approach to building trusted, Data, Analytics and AI-ready data systems. This repo hosts the Manifesto, Patterns, and the Trust Dashboard MVP.

A complete data mining project proposal and methodological blueprint for predicting the link between hypertension and psychopathologies in geriatric care, following the CRISP-DM framework.

R code for the discovery of COVID-19 subgroups by symptoms and comorbidities.

Find and fix data quality issues in your Last.fm scrobble history

Data Migration Quality Framework - A robust ETL pipeline with advanced anomaly detection for ensuring data quality during migrations

A web application for displaying automation test reports.

Ergebnisse der Datenanalyse vom Feinstaub Hackathon 2018 der Stuttgarter Zeitung

A comprehensive repository housing a collection of insightful blog posts, in-depth documentation, and resources exploring various facets of data engineering. From ETL processes and database management to orchestration tools, data quality, monitoring, and deployment strategies

LEILA - Librería de calidad de datos

Just what you expect from your electricity grid data

TellMeQuality is a tool for measuring Data Quality according to ISO/IEC 25024.

FIMUS imputes numerical and categorical missing values by using a data set’s existing patterns including co-appearances of attribute values, correlations among the attributes and similarity of values belonging to an attribute.