back_office_ops · workflow
Building a ChatGPT-powered business analytics assistant using multi-agent ReAct workflows
LLMs including ChatGPT are unreliable for quantitative reasoning on structured data, yet most critical business information resides in SQL databases, making analytics automation challenging.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · User poses analytical question
A user asks a complex analytical question about business data.
Tools used
ChatGPTStreamlitPlotlyPython ConsoleSQLiteSQL Server
Outcome
The article presents a methodology and reference implementation that turns ChatGPT into a business analytics assistant, enabling users to query structured data and receive visualized answers without advanced technical skills.
Source
https://medium.com/data-science-at-microsoft/automating-data-analytics-with-chatgpt-827a51eaa2c
Grounding & classification
Source type: technical build writeup
15 fields verified against source quotes, 1 dropped as unverifiable.
agentic workflowcode generationdata extractionmulti agent workflowhuman review describedtools describedworkflow describedtechnical build writeupback office opsagentic task execution