Big Data Management
Certificate Course - Mobility Systems Engineering - MSE.1.5.I26
| Date | Nov 18 - 19, 2026 |
| Duration | 2 days |
| Location | On campus - Karlsruhe |
| Language | English |
| ECTS | upon request |
| Cost | 1,550€ |
Fundamentals
Understand Big Data concepts, distributed systems, CAP theorem, and core principles of large-scale data processing and analytics.
Technology
Use cloud infrastructures, NoSQL systems, and distributed architectures to store, manage, and process large-scale datasets efficiently.
Applications
Apply Big Data tools for data integration, analytics, visualization, and real-world problem solving using large and complex datasets.
What you'll explore
- Explore the fundamentals of Big Data and its real-world applications
- Understand the “Vs of Big Data” and key system challenges
- Learn distributed system architectures and cloud computing concepts
- Study Brewer’s CAP theorem and its implications for system design
- Analyze NoSQL databases and their use cases
- Learn similarity metrics for data mapping and integration
- Explore large-scale data integration and analytics workflows
- Gain hands-on experience with cloud setup, querying, and visualization
Your key takeaways
-
Understanding of Big Data principles and system architectures
- Ability to explain CAP theorem and distributed system trade-offs
- Knowledge of NoSQL databases and cloud computing tools
- Skills in handling large-scale data integration and analytics
- Competence in applying similarity measures for data processing
- Practical experience working with Big Data systems and clous enviroments
Taught by recognized experts in Big Data Management
Benefit from the knowledge of leading specialists with extensive experience in research and industry. Their deep expertise guarantees a course of outstanding academic and practical quality.
Prof. Dr. York Sure-Vetter
Prof. Dr. York Sure-Vetter is Director of Information Process Engineering at Karlsruhe Institute of Technology (KIT) and a leading expert in Web Science, Semantic Web, Linked Data, and data-driven innovation. His research focuses on transforming data into actionable knowledge through text mining, service science, and intelligent information systems. After earning his degree in Industrial Engineering and a PhD in knowledge management at KIT, he held senior research and leadership roles at SAP and GESIS. He has also served as visiting professor at Stanford University and the University of Mannheim. Today, he combines academic excellence with leadership in national and international data infrastructure initiatives, advancing the future of data-driven research and digital knowledge systems.
Prof. Dr. Maribel Acosta
Prof. Dr. Maribel Acosta is a Junior Professor for Databases and Information Systems at Ruhr University Bochum (RUB) and a leading researcher in the fields of databases, Semantic Web, and artificial intelligence. Her work focuses on the efficient querying and management of knowledge graphs, combining advanced data engineering techniques with machine learning approaches. With a strong academic background and experience at leading institutions such as KIT and Heidelberg University, she contributes to the development of intelligent information systems and innovative data-driven technologies through research and teaching.
Dr. Lukas Heling
Dr. Lars Heling is Senior Knowledge Engineer in SAP’s Business AI Unit, where he works on intelligent data and knowledge driven systems for enterprise applications. He focuses on knowledge graphs, semantic technologies, and AI powered query processing to enable scalable and trustworthy data integration. With a strong background in research and industry, including Bosch, Stardog, and KIT, he bridges academic innovation with real world AI solutions and contributes to the development of future data driven expertise in industrial AI and semantic systems.
Who should attend
This course is particularly beneficial for professionals in the following fields
- Mobility systems and automotive engineering professionalsEngineers working on embedded systems, vehicle electronics, autonomous driving, and mobility technologies, focusing on system design, integration, and validation.
- Embedded systems and systems engineering specialists
Developers and engineers involved in model-based design, hardware/software co-design, real-time systems, and safety-critical electronic control systems. - Software, control, and simulation engineers in mobility applications
Professionals working with simulation, modeling, hardware-in-the-loop testing, and rapid control prototyping for complex technical systems. - Data, AI, and digital engineering specialists in mobility
Engineers and scientists applying data-driven methods, optimization, and computational tools to automotive and mobility system development. - Researchers and early-career academics
Master’s students, PhD candidates, and researchers in engineering, computer science, or mobility systems focusing on embedded systems, system architecture, and model-based engineering.
Advance your career with KIT-level expertise
Benefit from the reputation of the Karlsruhe Institute of Technology (KIT) while gaining practical skills, flexible learning opportunities, and a recognized certificate to support your long-term professional growth
Flexibility
Gain focused expertise in a specific field without committing to a full degree program, allowing you to build relevant knowledge efficiently and integrate learning seamlessly into your professional routine.
Relevance
Benefit from high-quality academic content combined with practical insights, delivered by experienced experts, supporting continuous, lifelong learning while ensuring direct applicability in real-world scenarios.
Advancement
Enhance your professional profile with a recognized certificate, demonstrating your commitment to ongoing development and supporting your career with tangible, verifiable credentials.
About HECTOR School
HECTOR School, the Technology Business School of the Karlsruhe Institute of Technology (KIT), is a leading provider of executive education in technology-driven fields.
For this course, participants who successfully complete the examination can earn a KIT certificate with ECTS credits, which may be credited toward our Executive Master of Science or Advanced Studies Programs, subject to content alignment.