Data Product Management Training Registration

Anmeldung Data Product Management Training

Anmeldung Data Product Management Training

Data Product Management Training

The training sessions are usually held in German. Please contact us if you are interested in training sessions in English.

Product managers are always on the lookout for opportunities to differentiate their products and to improve them for their customers.

With this in mind, major Internet platforms are increasingly using machine learning and AI methods to turn their data into products. In doing so, they are demonstrating that using data – whether in the form of standalone products or to enhance existing offerings – can be a valuable USP in the long term. The requirements for managing these data products are, however, different from the requirements for managing traditional products. 

This course explains the difference between traditional product management and data product management. Upon completion of the course, participants should be able to immediately implement the techniques learned in their own projects. This course teaches participants methods they can use to come up with ideas for their first data product and shows them how to prioritise lists of ideas. Other objectives involve testing market opportunities for their data products and managing portfolios of data products.


  • Data products: Types and business models
  • Using data products as USPs
  • The customer journey and formulating hypotheses
  • Value propositions for data products
  • Finding the problem/solution fit: Methods and examples
  • Determining the starting point and experimental design: Alternatives to off-beat algorithms
  • Developing a data strategy: How to obtain missing data
  • Data Value Chain: What are my current IT capabilities?
  • Feedback loop: Establishing USPs and generating training data
  • Data Value Matrix: Managing portfolios of data products
  • KPIs: The correlation between machine learning and business KPIs
  • Algorithms: Overview of the various algorithm types and application areas


  • The course fees include training materials, certificates of participation, lunches, drinks and snacks
  • Participants must bring their own laptop to the training sessions.


Dr Christoph Tempich is inovex’s Chief Data Economist, focusing on the economic aspects of the digital transformation and the strategic implications of a data economy. He supports companies from all sectors in establishing and improving digital business models, and particularly in designing and implementing data products. He gives presentations on the success factors of data products, on areas of application for machine learning and deep learning, and on the organisational changes resulting from the digital transformation. Dr Tempich received his doctorate in 2006 from the University of Karlsruhe, where his research focused on the use of artificial intelligence in knowledge management.