Understanding and using data: Your introduction to data literacy
First, data literacy. Then, AI literacy.
Strategy & basics
- What you can achieve with data in your workspace—and why data literacy is the foundation of AI.
- Understanding the building blocks of the data process: How data is generated, flows, and is used.
- Develop a structured approach to data-driven decision-making.
The structured data process
- Introduction to the CRISP-DM Model—a proven step-by-step method for data projects and AI initiatives. You'll learn how to plan and implement the first steps on your own.
Collect data: Source, structure & quality
- Identify relevant data sources and evaluate their quality—and understand why this is crucial for AI applications.
- Identify and prevent bias early on—in data and in AI results.
- Exercise: Analyze the sample data for bias.
Types of data analysis
- The Four Stages of Analysis—From Description to Prediction.
- Interpreting Numbers Correctly: Why Averages Are Often Misleading.
- Choose the chart that best fits your specific question.
- Exercise: Create meaningful visualizations and work with a dashboard.
Communication: Visualization & Data Storytelling
- Avoid misleading representations—through clear, honest visualizations.
- Telling compelling data stories—as a team or in front of stakeholders.
Ethical handling of data
- Data Protection, Bias, and AI Regulation: The GDPR and the EU AI Act Explained in Simple Terms.
- Identifying Typical Risks—and Why Ethical Data Literacy Is Essential for the Responsible Use of AI.
Summary & action plan
- Developing Concrete Next Steps: How to Integrate Data Literacy Directly into Your Daily Work.
In your online learning environment, you will find useful information, downloads and extra services for this training course once you have registered.
- You can reliably evaluate data sources—and determine which data you can trust.
- You will plan and independently implement the initial steps of a data project.
- You can identify biases in data and AI results—and you know how to avoid them.
- You create informative charts and visual analyses.
- You communicate data findings clearly and persuasively—through data storytelling.
- You understand the basic principles of data protection, bias, and the EU AI Act, and can identify typical risks.
Presentations are interspersed with group work, interactive exercises, and workshop sessions. Theory, discussion, and hands-on application ensure that you gain knowledge you can put to use right away.
- Employees without prior technical knowledge who want to make their work more data-driven and AI-ready.
- Professionals in marketing, controlling, or HR who regularly work with reports and data.
- Executives and project managers who want to better understand and manage data-driven and AI-powered decisions.
No prior technical knowledge is required. The focus is on easy-to-understand concepts and direct application—no prompting, no coding.
Want to dive deeper and understand how data needs to be structured for AI? The " training : The Right Data Foundation for Your AI Applications" is your next step.
Your Benefits at a Glance
Small groups—big learning success
Fully covered
- a shared lunch on each full- training day
- refreshments during breaks
All learning materials at a glance
42318
- Customized training courses
- Direct application in practice
- Efficient use of time and resources
Start dates and details

Thursday, June 17, 2027
09:00 am - 5:00 pm
Friday, June 18, 2027
08:30 am - 12:30 pm
- one joint lunch per full seminar day,
- Catering during breaks and
- extensive working documents.
- one joint lunch per full seminar day,
- Catering during breaks and
- extensive working documents.
Frequently Asked Questions (FAQ)
The training practical exercises for analyzing, visualizing, and communicating data. You will practice with sample data, create charts, and learn how to present results in a clear and understandable way. This will enable you to apply what you learn directly in your everyday work.
You don't need any prior technical knowledge. The training structured in such a way that the basics of data work are taught in an understandable way, so that even beginners can develop a solid understanding of data processes and tools.
After the training , you training independently plan the first steps of a structured data process, identify suitable data sources, and evaluate data quality. These skills will help you approach data-based projects methodically and implement them more successfully.
You will not only gain theoretical knowledge, but also practical exercises and an action plan that you can apply directly in your everyday work. This will enable you to continuously improve your data skills and successfully master data-based challenges in your profession.
Data literacy is important for many professional roles today, especially if you regularly deal with numbers, reports, or decisions. This includes employees without prior technical knowledge, specialists in areas such as marketing, controlling, or HR, and managers or project leaders who need to understand or steer data-based discussions. The training you training practical knowledge so that you can confidently tackle data-based issues and communicate better within your team.