Imagine asking your slack or team chat the same question you’d ask a BI tool, and getting back the exact rows, charts, or summary — instantly. No dashboards, no context switching, no waiting. This is the future: conversational database queries inside the tools your team already uses.
A few years ago, getting data meant opening a BI tool, remembering column names, and hoping the report was up-to-date. Today, collaboration can happen inside Slack and Teams which we are going to discuss furthur. Why should data live in a separate tab? When databases speak through chat, your workflow becomes conversational, collaborative, and fast.
instead of pinging an analyst and waiting hours, you ask in the slack channel: “How many active customers did we have last week?” — and the answer arrives as a message and with graphs, ready to discuss, react to, and share. That simple change speeds decisions and flattens the barrier between curiosity and insight.
Think of it this way:
- Non-technical users (finance, sales, HR, ops) often struggle with SQL, BI dashboards, or learning yet another tool.
- But Slack/Teams is where they already spend most of their day.
- If they can just type a natural question (like “What was our revenue last quarter?”) and Genie fetches the exact data from Databricks… that feels like magic.
What we built :
We connected Databricks Genie API in databricks to Slack app with a lightweight Flask service that sits between the two platforms. Here’s how it works technically:
Slack Input — A user mentions the bot or uses a slash command with a natural-language query (e.g., “show me revenue by region for last quarter”).
Flask Middleware — The request is captured by app, which verifies the Slack signature for security. It extracts the query text and prepares a call to Genie.
Databricks Genie API — Genie takes the plain-English question, interprets it into SQL using Databricks’ AI models, executes the query against the workspace, and returns structured results (tables, charts, or summaries).
Transformation — The app parses Genie’s response and converts it into Slack-friendly formats (text messages, blocks, attachments, or even file uploads if the dataset is large).
Slack Output — The response is posted back into the same channel where the question was asked, so the conversation stays uninterrupted.
Technical appendix — step-by-step for beginners
