data-reliability

Data Contracts engine for the modern data stack. https://www.soda.io

The dbt-native data observability solution for data & analytics engineers. Monitor your data pipelines in minutes. Available as self-hosted or cloud service with premium features.

re_data - fix data issues before your users & CEO would discover them 😊

This dbt package captures metadata, artifacts, and test results so you can detect anomalies, monitor data quality, and build metadata tables. It powers Elementary OSS and feeds the wider context layer used by Elementary Cloud’s full Data & AI Control Plane.

Code review for data in dbt

Metrics Observability & Troubleshooting

Installer and quickstart for DataKitchen's open-source DataOps TestGen and DataOps Observability. Installs TestGen with Docker Compose or pip, Observability with Docker Compose.

Swiple enables you to easily observe, understand, validate and improve the quality of your data

⚡ Prevent downstream data quality issues by integrating the Soda Library into your CI/CD pipeline.

This open-source Terraform provider enables users to seamlessly integrate the Monte Carlo data reliabillity platform into their infrastructure as a code (IaC) workflows.

DataBridge Quality Control

A schema contract guard for data pipelines. Detects, classifies, and reports schema changes in PostgreSQL databases.

Data Quality Tool

AI investigator for healthcare data pipeline incidents: read-only tools, mechanically verified evidence, calibrated abstention, human-approved remediation, and a 30-incident benchmark recorded from real pipeline runs (portfolio project)

AI-native open-source data reliability platform. Trust Score for every dataset.

LLM tool-calling data quality agent with read-only PostgreSQL, evidence guardrails, traces, evals, FastAPI, Docker, and CI-verified reports.

Azure real-time Data Engineering pipeline using Event Hubs and KQL, with stream reliability, state reconstruction, Gold serving, and operational observability.

Data Reliability Index is a Python package for attaching trust metadata to data, scoring reliability, and filtering records through explicit policies before they are used in analysis, APIs, or pipelines.

Production-minded FastAPI pipeline for validating, normalizing, deduplicating, and routing multi-provider data intake.

A living data reliability laboratory: observable streaming pipelines, data contracts, quarantine, replay, lineage and recovery.