Chris is a professor in Data Science and Analytics; his doctorate included Complex Adaptive Systems with Artificial Intelligence. At Deutsche Telekom he is involved with the development of the Telekom Data Intelligence Hub, a platform-as-a-service product, and responsible for Mobility Data Space and Analytics. Prior to joining Deutsche Telekom, he founded a business analytics startup, co-founded the Peter Drucker Customer Lab at Claremont Graduate University, and the Special Interest Group on Agent-based Systems of the Association for Information Systems (AIS) / “Wirtschaftsinformatik.” He began his career as a consultant with Accenture and later joined the faculty of the University of Southern California (USC) in Los Angeles. His research has been funded by Microsoft and Intel, among others; results have been published in leading publications, such as in journals of the Institute of Electrical and Electronics Engineers (IEEE), Information Systems Research and Communications of the ACM. Over the last two decades, Chris has become known for his success with data science and analytics for Fortune Global 100 clients in the US, Europe and China.
The European GAIA-X AISBL was founded, first C-level officers and the Board of Directors have been appointed. In Germany, a national data access point (MDP) and a data space (DRM) are under construction, both for mobility and both based on IDS technology to conform with GAIA-X. How fitting, then, to continue the momentum with the launch of an IDS Mobility Community.
Creating complete freedom to share data is the new commandment in business; this requires open data infrastructure standards like International Data Spaces (IDS) if it is to succeed in practice. Telekom experts report on first trials in the field and how the barriers to data-driven mobility and business models can be eliminated using innovative data spaces.
The artificial intelligence boom is highlighting the complexity of data: Different formats, vocabularies, rights – and usually not the right data and not enough. Data sharing could help. But there are worries about competitive disadvantage. Data spaces could be a solution. “IT Director” spoke to experts, including from Deutsche Telekom.
IDSA has developed a blueprint to enable companies to pool and share data for competitive advantage, while maintaining data sovereignty. The Telekom Data Intelligence Hub offers a first commercial implementation.
How to fix a problem like the coronavirus crisis, ultimately? With the right solution, medicine and vaccine. How do you find the right medication? Testing! How do you speed up the process? Simulation! But it has to be backed up with science and a rigorous experimentation process. Like we have done to identify solutions to the traffic problem in dense urban areas such as Berlin.
With 80 percent of the time budget spent on preparing rather than analyzing data, it looks like a fundamental flaw in the system. What to do? Maybe we can learn from the past: With his car factories, Henry Ford revolutionized the auto business. How if we started building data factories?
New last mile technology has arrived, think e-scooters, smart parking apps … but intermodal mobility hasn’t. Are there no benefits for the end-user? Let’s find out … with data science.
With all the attention on big data, it is easy to overlook the AI potential of small or unbalanced samples – or “small data”. Cloud trends like edge-computing open new opportunities.
Chancellor Merkel urged German enterprises to utilize the potential for value that lies in data, Otherwise, a rude awakening is to be expected. But how can the transition into a data-oriented organization succeed? To implement product management might be a good start.
We spend more than four years of our lives inside a car. If we are stuck in a traffic jam for 25 percent of the time, then we age 1 year faster … unless we spend the time in a useful way… maybe new technology can help.