CAS Data Competence for Business

This program is designed for professionals and managers who aim to leverage data for decision-making and value creation:

• Professionals and managers from business functions (e.g., marketing, finance, operations) who seek to better understand and contextualize data-driven challenges 

• Project managers and product owners involved in data, analytics, or AI initiatives 

• Professionals working at the interface between business, IT, and data teams 

• Individuals responsible for data-driven initiatives, digital transformation, or innovation 

• Decision-makers who want to assess and steer the use of data science within their organizations 

The focus lies on the use of data in a business context and on deriving informed decisions. For topics related to building and operating data infrastructures, the CAS Data Engineering offers a complementary specialization.

After completing this CAS, you will be able to:

• structure and clearly formulate data-driven challenges in a business context
• assess the opportunities, risks, and limitations of data science and contextualize them for business use
• identify relevant data sources and evaluate their potential for business processes
• understand and apply key concepts and methods in the data domain
• critically interpret results from analyses and models and translate them into decisions
• define and assess requirements for data quality, data management, and deployment
• effectively manage data-driven initiatives at the interface between business, IT, and data teams
• derive informed, data-driven decisions that support value creation and transformation

This module provides the conceptual foundations for working with data in a business context. It establishes a solid understanding of key concepts and relationships in the data domain and contributes to the “demystification” of data science. The aim is to systematically structure data-driven challenges and recognize the value of data for business processes.

Content:

• Core concepts and terminology in data science and the data domain 
• Paradigm shifts in data management 
• Roles and personas in data science 
• Integration of data into enterprise and IT architectures 
• Service-oriented architectures 
• Methods for structuring data-driven challenges 
• Identification and evaluation of data sources 
• Data collection techniques 
• Process analysis using business data 

Focus:
Developing a solid understanding of the value of data and the structured framing of data-driven challenges in a business context.

This module deepens the implementation perspective and demonstrates how data, models, and software are integrated into productive business environments. It provides an understanding of data management methods as well as the conditions required for deploying data-driven solutions effectively and sustainably .

The module is structured into two main areas:

Data by Design:

• Structuring data-driven challenges (problem framing) 
• Data risks, compliance, and governance 
• Data preparation and annotation 
• Data ingestion and data management 
• Data partitioning and scalability 
• Exploratory data analysis and quality assessment 

Deployment in Data Science:

• Feature engineering and modelling 
• Model tuning, evaluation, and selection 
• Software construction in a data context 
• Integration and deployment of data and models 
• Consumption of data products 
• Model operation and maintenance 

Focus:
Understanding how data and models are not only developed, but also effectively integrated into existing systems and sustainably applied in a business context.

The CAS is characterized by methodological diversity. In addition to lectures, presentations, (group) exercises, case studies or work on practical case studies, great importance is attached to the exchange of experience between participants.

The certificate of achievement consists of a project that accompanies the entire CAS and is worked on in groups. The project work is presented by the groups in a colloquium for each module and discussed in plenary.

The lectures take place on Friday and Saturday. Changes are possible.
 

• Prof. Dr. Pasquale Cirillo
• Dr. Mario Gellrich
• Dr. Christian Hitz
• Václav Pechtor
• Maria Rothstein
• Dr. Alexander Walter
• Dr. Michael Widmer

The certificate course is aimed at graduates of universities (FH/university) with at least three years of professional experience, as well as professionals without a university degree who have at least five years of professional experience and relevant further education qualifications (higher technical college or higher technical examination with a federal certificate/diploma).

Knowledge of English is required.
The course director decides on final admission.

Registrations will be considered in the order in which they are received.