Epic: AI-Powered Smart Metadata Insights & Auto-Tagging System

[Anuragkumar101]

• Is your feature request related to a problem? Please describe.
Currently, users of OpenMetadata need to manually explore datasets, apply tags, and understand lineage or metadata relationships. This process becomes time-consuming and inefficient, especially in large-scale data environments.
There is no intelligent system that proactively helps users understand their data or suggests improvements, which leads to slower onboarding and reduced productivity.
• Describe the solution you'd like
I propose an AI-powered feature that enhances metadata discovery and management by introducing:
🔍 Smart Metadata Insights
Automatically analyze datasets and provide summaries, usage patterns, and potential data quality issues.
🏷️ Auto-Tagging System
Suggest and apply tags based on schema, column names, and data patterns.
🔗 Intelligent Lineage Explanation
Provide human-readable explanations of lineage (e.g., “This table depends on X and Y transformations”).
⚡ Context-Aware Recommendations
Suggest joins, related datasets, or frequently used tables.
🤖 Optional chatbot-like assistant inside OpenMetadata UI for querying metadata in natural language.
• Describe alternatives you've considered
Manual tagging and documentation (current approach)
External tools for data discovery (adds complexity and fragmentation)
Static dashboards without intelligence
These alternatives lack automation and require significant manual effort.
• Additional context
This feature would significantly improve:
User onboarding experience
Data discoverability
Productivity of data engineers and analysts
It aligns well with modern AI-driven data platforms and could position OpenMetadata as a next-generation intelligent metadata system.
Related issues
Could be related to existing enhancement issues around tagging, lineage, and UI improvements
Potential integration with ingestion and profiler modules

[Sngithub12]

Thanks for laying out that feature idea. It seems like it really hits on some of the main issues with how metadata gets used right now.

I want to help out with this if I can. Just to make sure I am on the right track, could you clarify the overall scope and how it would fit into OpenMetadata's setup.

One way to break it down for getting it done might be starting with smart metadata insights. That could mean adding to the profiler or ingestion parts to pull together summaries of datasets, like patterns in schemas or how much data is missing, or even signals on usage. Then store those as extra metadata bits.

Auto tagging sounds useful too. Maybe mix rules with some machine learning help, looking at column names, types, and patterns in the data. It would tie into the classification and tag stuff already there.

For lineage, there is the explanation side. I am thinking a service that turns those graphs into something people can actually read. Probably as an API built on the lineage models we have.

Recommendations that make sense in context could come from query logs, lineage, and patterns where things show up together. Suggesting related datasets that way.

The AI assistant part feels like it could wait, maybe phase two. Natural language for asking about metadata, hooked up to the APIs and some LLM in the back.

As for questions, what do you think is the easiest way in for someone contributing, like tagging or lineage or the insights? Are there any talks or work already going on for AI help with metadata? And would it be better to do small PRs one feature at a time, or put together a bigger proposal first.

I am fine jumping in with something smaller, say auto tagging or the lineage explanations, and then adjust from there based on what you say.