Repository Index

The Open Context Layer for Data and AI , OpenMetadata is the open platform for building trusted data context and business semantics for humans, AI assistants, and agents.

• metadata
• datadiscovery
• dataquality
• data-profiling

1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.

• pandas-profiling
• pandas-dataframe
• statistics
• jupyter-notebook

Evidently is ​​an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.

• data-drift
• jupyter-notebook
• pandas-dataframe
• machine-learning

Build data pipelines with SQL and Python, ingest data from different sources, add quality checks, and build end-to-end flows.

• analytics
• bigquery
• data-modeling
• data-pipelines

Canonical GTFS Validator project for schedule (static) files.

• gtfs-dataset
• gtfs-validator
• gtfs-zip
• gtfs-feed

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-ops
• data-quality
• data-quality-checks
• data-quality-measurement

Declarative data quality engine. Define checks in YAML, run anywhere.

• airflow
• anomaly-detection
• data-contracts
• data-quality

A detective for your data. Zero-config data quality monitoring — works with dbt, Postgres, BigQuery, Snowflake. No YAML.

• anomaly-detection
• bigquery
• cli
• data-engineering