#Data-observability
Showing 20 of 20 repositories tagged #data-observability, ranked by stars
The Context Platform for your Data and AI Stack
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 😊
First open-source data discovery and observability platform. We make a life for data practitioners easy so you can focus on your business.
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
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.
Official Monte Carlo toolkit for AI coding agents. Skills and plugins that bring data and agent observability — monitoring, triaging, troubleshooting, health checks — into Claude Code, Cursor, and more.
Swiple enables you to easily observe, understand, validate and improve the quality of your data
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
Soda Spark is a PySpark library that helps you with testing your data in Spark Dataframes
DataOps Observability is part of DataKitchen's Open Source Data Observability. DataOps Observability monitors every data journey from data source to customer value, from any team development environment into production, across every tool, team, environment, and customer so that problems are detected, localized, and understood immediately.
DataOps Observability Integration Agents are part of DataKitchen's Open Source Data Observability. They connect to various ETL, ELT, BI, data science, data visualization, data governance, and data analytic tools. They provide logs, messages, metrics, overall run-time start/stop, subtask status, and scheduling information to DataOps Observability.
Never sift through endless dbt™ logs again. dbt Command Center is a free, open-source, local web application that provides a user-friendly interface to monitor and manage dbt runs.
:zap: Prevent downstream data quality issues by integrating the Soda Library into your CI/CD pipeline.
Declarative data quality engine. Define checks in YAML, run anywhere.
Long-form article introducing Decision Safety: a trust gate between dashboards and actions. Defines four pillars (coverage, freshness, stability, measurement risk), proposes a Decision Safety Score (0–100), shows common failure modes, and includes a copy-paste “Decision Safety Contract”+checklist to block unsafe decisions without hiding dashboards.
A long-form, practical article on data coverage: why clean dashboards still lie when datasets don’t represent the full calendar or population. Includes definitions, real failure modes (joins, filters, late data), coverage metrics, visualization patterns, anomaly/forecasting pitfalls, and reusable checklists.