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Data Engineering
Join discussions on data engineering best practices, architectures, and optimization strategies within the Databricks Community. Exchange insights and solutions with fellow data engineers.
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Reducing Time to Help in the Databricks Community

Brahmareddy
Esteemed Contributor II

Hi @MandyR , @Advika , and team

I wanted to share one idea for the Databricks Community. Can we explore a Genie-like experience for databricks community?

The Community already has many useful answers, accepted solutions, blogs, MVP articles, and discussions. But sometimes members may not find the right answer quickly. They may not know the exact keywords to search, or they may post a new question even when a similar answer already exists.

A Genie-like community assistant can help members find the most relevant answers faster.

For example, if someone asks about Unity Catalog permissions, Delta tables, PySpark errors, Auto Loader, Databricks SQL, Lakeflow, MLflow, or any Databricks feature, the assistant can search the Community content and suggest the best matching answers, accepted solutions, related articles, and documentation links.

This can help in many ways:

It can reduce duplicate questions.

It can reduce the time community members spend answering repeated questions.

It can help users get support faster.

It can make existing accepted solutions easier to find.

It can guide users to ask better questions with the right title, tags, error message, code snippet, and context.

In my view, this should not replace community discussions. It should support them.

The assistant can first suggest matching answers. If the user still needs help, it can guide them to post a better question with all the needed details.

The goal is simple: help every member reach the right answer faster and make the Community knowledge base more useful over time.

I am happy to ideate more and share inputs from a user and contributor perspective, including possible workflows, use cases, and POC ideas.

Would this be something the Community team can explore?

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