open-metadata / OpenMetadata

2021-08-01 · Source: Github Trending: All languages · Field: Technology & Digital — Data Science & Analytics, Cloud Computing & IT Infrastructure, Cybersecurity & Data Privacy · Depth: Intermediate, quick

Summary

OpenMetadata is an open-source, unified metadata platform designed for data discovery, observability, and governance. It features a central metadata repository, column-level lineage, and team collaboration capabilities. The platform is built on Open Metadata Standards and APIs, supporting over 84 connectors for various data services, including data warehouses, databases, and dashboard services. Its architecture comprises Metadata Schemas for definitions, a Metadata Store for graph management, Metadata APIs for integration, and an Ingestion Framework for data source connectivity. Key functionalities include advanced data search, real-time collaboration tools, no-code data quality testing with interactive dashboards, and automated data classification for governance.

Key takeaway

For CTOs and VP of Engineering evaluating data management solutions, OpenMetadata offers a comprehensive, open-source platform to centralize metadata, improve data quality, and enforce governance. You should consider its 84+ connectors and robust collaboration features to streamline data operations and enhance trust in your data assets across the organization.

Key insights

OpenMetadata unifies data discovery, observability, and governance through a standardized, collaborative platform.

Principles

• Metadata standardization is crucial.
• Collaboration improves data quality.
• Automation enhances data governance.

Method

OpenMetadata uses a four-component architecture: Metadata Schemas for definitions, a Metadata Store for graph management, Metadata APIs for integration, and an Ingestion Framework with 84+ connectors for diverse data sources.

In practice

• Use keyword search for data discovery.
• Define no-code data quality tests.
• Integrate with Slack via webhooks.

Topics

• Data Governance
• Data Discovery
• Data Observability
• Data Lineage
• Data Quality

Code references

• open-metadata/OpenMetadata

Best for: CTO, VP of Engineering/Data, Data Engineer, Data Scientist, MLOps Engineer

Related on AIssential

• From Context to Semantics: How Metadata Powers Agentic AI — Metadata platforms are evolving into semantic context layers crucial for precise AI and agentic system outcomes.
• Data Quality as Metadata — Checks, Profiles, and Contracts Derived From Structure — Treating data quality rules as metadata enhances visibility, propagation, and robustness over ad-hoc SQL queries.
• Backstage with Lakebase, part 2 — Unified governance for operational databases simplifies security, compliance, and cost attribution while enabling rapid development workflows.
• DuckLake 1.0: Data Lake Format with SQL Catalog Metadata — DuckLake 1.0 centralizes data lake metadata in a SQL database, improving performance and simplifying operations.
• Your LLM issues are really data issues — Inconsistent data and weak governance undermine analytics and ML, necessitating AI-ready data practices.
• OpenTelemetry Project Publishes “Demystifying OpenTelemetry” Guide to Broaden Observability Adoption — OpenTelemetry provides vendor-neutral instrumentation and data collection, requiring separate backend systems for full observability.

Open in AIssential →

Editorial summary, takeaway, and curation by AIssential. Original article published by Github Trending: All languages.