Data Analysis Agents for Spreadsheets and SQL
Use or build agents that query data, run analysis and explain results you can actually verify
A taste of a lesson
The agent says our average order value doubled last month. Nothing else changed. Should I believe it?
Be suspicious first. A sudden doubling with no business change usually points to the query. Ask to see it and check whether it joins orders to order items or payments. If so, each order may be counted once per line, inflating totals while the order count stays right. Also check whether last month includes test orders, refunds or one unusually large purchase. Compare with your finance report for the same month. Exercise: what is the order count the agent used, and does it match your shop dashboard?
Written by the teacher as an example. In your lesson the tutor answers your own questions, and like any AI it can be wrong.
What you will be able to do
- Describe how data agents write, run and explain queries or code
- Provide schemas, metric definitions and business rules as agent context
- Catch common errors such as duplicating joins and wrong date fields
- Set up read only, limited and logged data access for agents
- Present agent results with definitions, method and caveats visible
Lesson plan
- 1 How data agents work Follow the loop from question to query to result to explanation. Start
- 2 Context that prevents wrong answers Give the agent the definitions and rules it cannot guess. Start
- 3 The classic data mistakes Recognise errors that produce plausible but wrong numbers. Start
- 4 Verification habits Check agent results quickly before anyone relies on them. Start
- 5 Safe access Connect agents to data without risking damage or exposure. Start
- 6 Presenting results honestly Share agent analysis with its definitions, method and limits clear. Start
Try asking
About this tutor
For analysts, operations staff and developers who want an agent to answer questions about data in spreadsheets or databases. Data agents write queries or code, run them and explain the results, which is powerful and risky in equal measure: a plausible chart can rest on a wrong join or a misread column. You will learn how these agents work, how to give them the context they need (schemas, definitions, business rules), how to check their queries and numbers, how to keep access read only and safe, and how to present results with their assumptions visible.
Reviews
4.3
3 ratingsSample
- Zainab O.Sample
Clear explanations even for someone with basic SQL. The safe access lesson helped me convince IT to set up a read only replica.
- Ethan P.Sample
Writing down our metric definitions took an afternoon and improved the agent's answers more than any prompt tweak. Good, practical course.
- Carmen R.Sample
The duplicating join example was exactly our bug. I now check row counts before trusting any agent query.
About the teacher
I help teams turn agent ideas into useful assistants for support, research and data work
9 tutors 315 lessons taught Sample
I work on the practical end of agents: the support assistant that answers customers, the research helper that reads and cites, the analyst that queries a database and explains what it found. I spent a long time in customer facing technical roles, so I care about what the person on the other side experiences, not only about what the model...
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