Exploring the World of Data and Artificial Intelligence in Business
Dive into Data Science and Business Intelligence with our training course “Exploring the World of Data and Artificial Intelligence in Business”, which clarifies complex concepts, helps participants understand the importance of data and AI in today’s business world. It also equips them with the skills to leverage data-driven insights for effective decision support and understand the possibilities of AI in today's business landscape.
This training is designed for a broad audience, including:
Managers, leaders and professionals in the following areas:
Finance and Controlling
Supply Chain and Procurement
Marketing
Sales and Commerce
HR
Our training is also recommended for senior leaders of SMEs, entrepreneurs, and individuals who are new to the fields of Data Science and Artificial Intelligence and are eager to understand the basics. Essentially for anyone who is curious and interested in these rapidly evolving disciplines.
Participants will:
Learn the key data and AI concepts and their importance
Understand how to utilize data within their own organization
Gain practical data management perspectives and strategies that work in real life
Learn how Business Intelligence (BI) can support their business and help seize opportunities
Acquire general knowledge about machine learning and AI, and how to use them
Develop a business-focused perspective to utilize data-based solutions
Explore real-world examples used by companies and apply them across various business areas (e.g., commercial reporting, finance, campaign management, HR, business performance management) and sectors
Learn from instructors who bring experience from numerous data-related projects
Topics
- Part 1: Theory
- Part 2: Use Case Examples
Part 1: Theory
Introduction
The importance of data, global trends and shift in perspective
Where data comes from, how it is processed and stored
What is Data Analysis and Data Science?
Business Intelligence and Business Dashboards
Data architecture and data models
What does a Data Analyst, Data Scientist, Data Engineer and Data Architect do?
Data Literacy and Data Culture
The significance of Data Literacy for businesses
Key steps to build Data Knowledge
How to establish / strengthen Data Culture and organizational Data Literacy?
Business Intelligence and Data Analysis
What is BI and how is it used?
Problems BI can solve
Types of analytics
Common use cases in business
From Data Collection to Data Storytelling
Data projects, and how to succeed
Principles of data visualization, best practices, and pitfalls to avoid
Future trends in data leverage and utilization
Machine Learning and Artificial Intelligence
Programming languages
Required mathematics
Data preparation
Machine learning algorithms and libraries
Generative AI introduction
Generative AI
Foundation Models: theory, architectures, and applications from language to vision
Available solutions, current and future trends, typical business applications
Legal aspects of Artificial Intelligence
AI Act, liability issues, risks
Data Protection (GDPR), confidentiality, copyright, and other legal considerations
Part 2: Use Case Examples
Estimations and Forecasts (Regression)
Value estimations
Revenue and volume forecasts
Commercial Modeling
From simple to complex: trend analysis, variance analysis, and price-volume analysis
Pricing analysis
Price elasticity example
Optimization Tasks
Cash optimization example (Cash Management system)
Customer Analytics
Basic customer analytics
Customer segmentation (clustering), loyalty and customer value
Financial Analysis
What does the future P&L or 360-degree P&L look like?
Financial modeling
Other data applications in finance
Business Performance Analysis
Strategic pillars and KPI trees (finance, operations, HR, green agenda, customer focus, etc.)
Power BI cards for KPI objectives
Linking leading and underperforming KPIs in the analytical context
HR Analytics
Work time and attendance analysis, overtime and workload
Absence analysis and vacation reporting
Practical exercise
Customer churn modeling example, interpreting and applying results (classification and customer retention)
Training Information
Location: online
Language: English
Date: 14-15 October 2025
Duration: 2x4 hours (9:00 AM – 12:15 PM CET)
Fee: 400 EUR + VAT / person
Registration
