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Data Analytics Foundation
Without data literacy, little moves forward today. This introductory course shows how raw data points become real decision-making foundations – clear, efficient, and directly applicable in modern organisations.
Key topics
- Roles, working methods, and workflows in data analytics.
- Data types, quality checking, preparation, and exploration.
- Core statistical concepts and understandable forms of visualisation.
- AI-supported analysis methods in a practical context.
- Modern tools for structured and traceable analyses.
Prerequisite
A basic understanding of digital working environments is sufficient – no prior knowledge of statistics or IT is required.
Target group
Anyone who wants to better understand, contextualise, and actively shape data-based decisions in their professional field.
The result is a clear picture: how data moves from raw form to usable insight – and what that means for your own work.
course content
From data point to insight
- Key terms and processes in data analytics.
- Business intelligence (BI) in overview.
Capturing and structuring data
- Methods for data collection.
- Data storage and organisation.
- Variables and data structures.
Ensuring data quality
- Data scrubbing and cleansing techniques.
Analysing and interpreting data
- Statistical fundamentals and methods.
- Data mining and data analysis.
- Machine learning in an analytics context.
- Understanding algorithmic approaches.
Making data visible
- Explanatory and exploratory visualisation.
- Choosing the right chart types and plots.
- Design principles and tool overview.
Up to 100% funding for your continuing education
Attractive funding opportunities are available for numerous continuing education programs – depending on the funding program, up to 100% funding is possible.
The requirement is that you live or work in Germany. Our funding opportunities are not available outside of Germany.
Funding opportunities are available for career starters, job seekers, career changers, startups, experienced professionals, those seeking career advancement, and specialists.
What background do you need for Data Analytics Foundation?
- IT or statistics knowledge is helpful but not required. The course is designed so that people without a technical background can follow along with ease.
What makes Data Analytics Foundation stand out?
- The focus is on applicable fundamentals rather than abstract theory. The combination of technology, analysis, and data ethics is compact, current, and directly usable across many industries.
What competencies does Data Analytics Foundation build?
- Covers working with data sources, preparation steps, statistical analysis, visualisation, and data-driven decision-making.
Is Data Analytics Foundation useful outside IT roles?
- Yes – the certificate is valuable across all sectors. In marketing, HR, procurement, or controlling, it helps you read, question, and factor data into decisions more confidently.
What does further training in data analytics actually deliver?
- Training builds analytical thinking and methodological knowledge, makes working with tools and data sources easier, and provides a solid foundation for digital transformation projects.
What is the difference between data analytics and data science?
- Data analytics focuses on interpreting and using existing data. Data science goes further – with programming, complex models, and algorithm development.
How long is the Data Analytics Foundation certificate valid?
- The certificate has no expiry date – recertification is neither planned nor required.
