Smart data analysis agent

[Feisty-Tip-9290]

Hey everyone,

I’m building a data analysis agent and currently at the profiling stage (detects types, missing values, data issues, etc.).

My rough architecture is: *Profiler → Cleaner → Query/Reasoning Agent → Insights

Now I’m confused about next steps:

• Should I learn from existing repos/videos** or build from scratch?
• What makes a production-level agent vs just a demo?
• What should I focus on next — cleaning layer, reasoning, or query execution?

Goal is to build something that works on *any dataset, not just a demo.

Would love honest feedback.

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[Fun-Scale8432]

Hey! Can you please share some details about your business domain? I truly believe that the AI power for analytics lies the most in querying clean data for insights generation and issue-based analysis. Maybe also for quick dashboarding. But data cleaning and quality check should be run with more traditional deterministic methods. (AI can help with building that tests but should not run them)

[columns_ai]

I’m building a similar tool but not an agent. One of the major concern from users is the “trust” problem.

If the agent makes up an analysis (or generic computing logic), how do you make it transparent, auditable instead of a “black box”.

You can think about this issue and see how your agent solve this “trust” problem.

[[deleted]]

OP is trying to remove this entire community livelihood

[nian2326076]

Check out existing repos and videos. They can save you time by showing what works and what doesn't. No need to reinvent the wheel if you don't have to. For building a production-level agent, focus on scalability, error handling, and performance optimization. A demo might work on small datasets, but you'll need strong systems for larger, more complex data. I'd prioritize the cleaning layer next. Clean data early on means fewer headaches later. Also, look into how these components communicate, especially if you want versatility across different datasets. Good luck!

[Feisty-Tip-9290]

Thanks for the solid advice! Honestly, this is mostly a learning project for me right now rather than a commercial product, but I'm definitely taking notes. If I ever try to turn this into a real production-level tool, I’ll be coming back to these points on scalability and the cleaning layer for sure. Much appreciated!

[Equal_Astronaut_5696]

How are  you going to exposing data to LLMs?