Training course · Claude Code · Data Analysis & Excel

Claude Code for Data Analysis and Excel

Agentic coding with Claude Code in the terminal and IDE: CLAUDE.md, subagents, hooks, MCP, CI pipelines and secure permissions.

Duration
2 days (14 hrs)
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

This course connects Claude Code with the everyday processes of Data Analysis & Excel. Participants work on realistic scenarios and leave with prompts, workflows and checklists they can use straight away.

Claude Code is not only for professional developers. Business users with no programming background can use it to analyse data, clean up Excel and CSV files, generate reports or build small internal tools, all in plain language. You describe what should happen, and Claude Code writes and runs the necessary scripts itself. This course variant shows you how to put these capabilities to work in your daily job without needing to understand code, and how to check the results reliably before anyone relies on them.

You will work through realistic office scenarios: merging exports from several systems, producing analyses with charts, generating documents and mail merges automatically, or turning repetitive file chores into a single command. Working safely is a central theme: which data may be processed, how you stay in control of approvals, and when to involve your IT department. The result is a set of useful helpers that take load off your team while remaining transparent and easy to hand over.

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.

The course is delivered live – either online in a virtual classroom or on-site in our training rooms in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart and Kaiserslautern. We can also run it exclusively for your team.

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

What you will be able to do

  • You commission data analyses and file tasks from Claude Code in plain language.
  • You clean and combine Excel and CSV data and check the results for plausibility.
  • You automate recurring document and reporting tasks with reusable instructions.
  • You have small internal helper tools built and refine them step by step.
  • Create and understand complex Excel formulas, Power Query steps and macros with AI.
  • Clean, analyse and visualise data faster and more transparently with AI support.
  • Automate recurring reports and check AI results methodically for accuracy.

Course outline

Day 1

Module 1 Getting started without coding skills
  • What a coding agent is and what it is allowed to do on your computer
  • Launching Claude Code and setting up a protected working folder
  • Describing tasks in everyday language: goal, input files, expected result
  • Understanding approval prompts and consciously accepting or declining them
Module 2 Analysing data in Excel and CSV files
  • Cleaning exports: duplicates, date formats, missing values
  • Combining several tables and calculating key figures
  • Producing charts and summaries as Excel files or images
  • Sanity-checking results with spot checks and cross-calculations
Module 3 Automating documents and routine tasks
  • Generating reports, minutes and mail merges from templates and data
  • Renaming, sorting and converting files automatically
  • Saving recurring procedures as reusable instructions
  • Writing a simple team guide in CLAUDE.md
Module 4 Building small scripts and internal tools
  • From idea to working helper: stating requirements clearly
  • Having simple input forms or local web interfaces created
  • Improving step by step: describing problems instead of debugging yourself
  • Documenting results so colleagues can use them

Day 2

Module 5 Working safely and responsibly
  • Handling personal and confidential data correctly
  • Limiting permissions and working only in approved folders
  • Recognising limits: when a tool should be handed over to IT
  • Coordinating with IT, data protection and business owners
Module 6 Hands-on project: your own solution for Data Analysis & Excel
  • 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.
Module 7 Data protection, quality & transfer to daily work
  • 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.
  • Ground rules for safe AI use in your team
  • Checking results: facts, sources, tests and the four-eyes principle
  • Personal action plan for the next 30 days
  • Open questions, outlook and resources for further learning

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.

Prerequisites

No programming knowledge is needed; confident use of Excel, files and folders on your own computer is sufficient. Confident everyday use of Excel; no programming skills required.

Technical requirements

Your own laptop with admin rights, Git, a Node.js runtime and an up-to-date editor; a Claude subscription or Anthropic API access is required for the exercises.

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.

Suggested dates

All dates are suggestions – your preferred date is always possible.

  • Tue, 24 November 2026 – Wed, 25 November 2026 Online Request
  • Mon, 30 November 2026 – Tue, 1 December 2026 Hanover Request
  • Mon, 14 December 2026 – Tue, 15 December 2026 Online Request
  • Mon, 11 January 2027 – Tue, 12 January 2027 Online Request
  • Wed, 20 January 2027 – Thu, 21 January 2027 Munich Request
  • Tue, 26 January 2027 – Wed, 27 January 2027 Online Request

Frequently asked questions

How is Claude Code different from traditional code completion?

Code completion suggests the next few lines, whereas Claude Code acts as an agent that handles whole tasks: it searches the repository, plans changes across several files, runs tests and commands, and corrects itself based on the results. You define the goal and review the outcome instead of steering every single line yourself.

Is Claude Code secure enough for enterprise use?

By default, Claude Code asks for approval before editing files or running commands. Permission rules, sandboxing, managed settings and hooks let you define precisely what the agent may do. During the course you learn to configure these mechanisms to match your security and data protection requirements and to assess risks such as prompt injection.

Does Claude Code work with my language and tech stack?

Yes. Claude Code is language-agnostic because it works with files, terminal commands and your existing build and test tooling. Whether you use Python, Java, TypeScript, Go, SAP-related code or infrastructure as code, what matters most is a well-written CLAUDE.md describing your commands and conventions. Each course variant adds the relevant domain focus.

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.

How much does “Claude Code for Data Analysis and Excel” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 2 training day(s) with a live trainer, course materials, a lab environment and a certificate of attendance.

Can I suggest my own date?

Yes. Our suggested dates are just a guide. In the request form you can always describe your preferred date or period in free text – we check availability and confirm within one working day.

Is the course online or on-site?

Both are possible: live online in a virtual classroom or on-site in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart or Kaiserslautern. We can also run the course exclusively for your team.

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