Business fields · Data Analysis & Excel
AI training for Data Analysis and Excel
In almost every department, decisions are made on the basis of spreadsheets, exports and reports – and much working time goes into cleaning, combining and analysing that data. Generative AI dramatically lowers the barrier to sophisticated analysis. It explains and writes Excel formulas, builds Power Query steps and macros, suggests pivot analyses and charts, generates Python or SQL code for larger datasets and drafts commentary on KPIs. AI agents can prepare recurring reports automatically. This empowers business users to answer questions themselves that once meant waiting for IT or an analytics team. What remains essential is checking results rigorously and keeping an eye on data quality.
Who is this course for?
- Business users who work regularly with Excel and reports
- Controllers and finance staff
- Sales and marketing analysts
- Business analysts and reporting teams
- Team leads responsible for KPIs
Typical challenges we address
- Time-consuming manual data cleaning and copy-and-paste processes
- Complex formulas and macros that only a few people understand
- Data from different systems in inconsistent formats
- Error-prone spreadsheets without traceable calculation logic
Practical scenarios from your field
Writing and explaining formulas
AI creates formulas such as XLOOKUP, SUMIFS or dynamic arrays from a plain-language description and explains existing nested formulas step by step. Common pitfalls are pointed out as well.
Cleaning and combining data
For inconsistent exports, AI suggests cleaning steps, builds Power Query queries or scripts for merging, de-duplicating and normalising, and documents the transformations. The steps can be repeated with one click next time.
Analyses and charts
From a business question, AI derives suitable pivot tables, metrics and chart types and helps present results clearly and accurately. Misleading displays such as truncated axes are avoided.
Python and SQL for large datasets
When Excel reaches its limits, AI generates Python or SQL code for analysing larger datasets, which business users run, understand and adapt step by step.
Commenting on KPIs
Variances, trends and anomalies in reports are translated into clear written commentary for management and departments; hypotheses about causes are checked by experts. Reports become self-explanatory in meetings.
Automating reports
Recurring monthly or weekly reports are automated with macros, scripts or AI agents so that data is retrieved, prepared and distributed as a report. Manual steps and transfer errors largely disappear.
Possible hands-on projects
CSV cleaning app
A small web app that reads CSV files, detects duplicates, blank rows and format errors and outputs a cleaned file with a change log.
KPI dashboard
An internal dashboard that reads monthly exports and displays key metrics interactively with prior-period comparison and RAG logic. Filters by region, team or product simplify analysis.
Formula explainer
A tool into which a complex Excel formula is pasted and which breaks it down into understandable steps and documents it.
All 15 courses for Data Analysis and Excel
AI for business (12)
- ChatGPT for Data Analysis and Excel
- Claude for Data Analysis and Excel
- Microsoft 365 Copilot for Data Analysis and Excel
- Google Gemini for Data Analysis and Excel
- AI Agents for Data Analysis and Excel
- Prompt Engineering for Data Analysis and Excel
- Generative AI for Data Analysis and Excel
- n8n for Data Analysis and Excel
- Make for Data Analysis and Excel
- Perplexity for Data Analysis and Excel
- Mistral Le Chat for Data Analysis and Excel
- EU AI Act & AI Compliance for Data Analysis and Excel
Vibe & agentic coding (3)
Data protection & compliance
Spreadsheets often contain personal data about customers or employees as well as confidential business figures, which may only be processed in approved AI environments and ideally anonymised or aggregated. Analyses relating to employees may be subject to works council rights, and responsibility for the accuracy of reports remains with the business unit.
Prerequisites
Confident everyday use of Excel; no programming skills required.
Frequently asked questions
Do I need programming skills for data analysis with AI?
No. Good Excel skills are enough to start. AI generates formulas, Power Query steps and, where needed, Python code that you learn to follow step by step. What matters is being able to sanity-check results. The course focuses on exactly these checking techniques alongside hands-on practice.
How reliable are AI-generated formulas and analyses?
Often very good, but not flawless: references, edge cases or wrong assumptions about the data structure lead to silent errors. That is why you verify results with spot checks, control totals and cross-calculations. The course teaches a simple checking routine to apply to every AI-assisted analysis.
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