For Mobility Analytics only ... for the data scientist in mobility ... for the data scientist’s manager ... for the manager’s boss ... Insights on GAIA-X, IDSA, NPM, RL-HH, MDP, DRM, Catena-X …
T-Systems is Germany’s leading IT-service provider for the automotive industry. Clients benefit from reliable operations of global backend systems (EU, US, China), leading innovation and super-fast 5G and edge communications.
Stop wasting time processing your data - start experimenting! Join the data sandbox to create results faster by benefiting from experiments with free data types & better data. In data analytics today, more than 80% of the time budget is spent on data processing alone. With the “data sandbox” you can generate results faster.
How do I manage and share my data, how can I analyze it? These are not new questions. But how can I accomplish these tasks under the assumption that I retain full sovereignty over this data on the one hand, but on the other hand build data spaces on a federated architecture approach? These are current challenges in the data space environment.
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.
The Telekom Data Intelligence Hub platform-as-a-service product (PaaS) is being used by TU Dortmund University to enable Master's students in the Mechanical Engineering faculty to gain practical experience of data and information management in teams.
Deutsche Telekom organized the #AIHack4Mobility on March 18th and 19th. After the success with #AIHack4Diversity in 2019 (link) and #AIHack4Ladies 2018, this year everything revolved around the topic of "Future Mobility" under the motto "Artificial Intelligence for Diversity Teams".
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.
The FAZ has received a new draft law for the sovereign handling and exchange of industrial data within the EU. The motivation behind the new edition is based on the endeavor to enforce valid European laws within data security and on the other hand it is based on the long-term goal to create an independent and innovation-promoting European data space.
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.
HERE is a leading provider of mapping and location data and related services to individuals and companies covering sectors such as Automotive, Public Sector & Infrastructure, Transportation & Logistics. Their data assets are widely used for developing applications that enable safer driving, optimization of last-mile delivery including the enablement of real-time visibility within supply chains.
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.
Germany’s automotive industry has been its economic powerhouse for years. Now, its own success may be a problem. Cities are full of cars; traffic is getting worse … Plus digitalization and new technology are transforming the business.
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?
Hollywood already invented them: avatars, cyborgs, androids, clones. Today, leading politicians, managers and investors speak about the Digital Twin as a reflection of people as something perfectly natural. But where remains the data sovereignty?
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.
Telekom Data Intelligence Hub at Europe’s biggest data science conference by Data Natives, a community of 70.000+ data experts. Telekom is presenting with partners IBM and IDSA.
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.
No longer missing out on innovation … Startup Autobahn presents a curated lineup of start-up stars to select automakers and suppliers in the automobility ecosystem.
Automotive revenue is shifting to mobility services and power – and profit – will shift from the vehicle – or hardware – to data: A rerun of a story foretold in Rappaport & Halevi’s “The Computerless Computer Company” in a 1991 Harvard Business Review article?
Every two years Daimler invites its top suppliers for two days of exhibits, keynotes, presentations and expert talks: New developements with connected, autonomous, electrified and shared automobility.
At the moment, roads and parking dominate the scenery of inner cities. The arrival of new forms of mobility, however, will radically alter the consumption of urban space.
Mistakes and errors slow down production and cost money. How to prevent it? Wouldn't it be ideal to identify defects prior to production? “Frontloading” with digital twins can do the trick.
There is a lot of open-source data out there, for instance on population density and means of transport. However, a differentiated picture and prognosis are only possible with dynamic data on movements.
Obtaining the right data in the right amount is key to AI success. However, on their own very few companies will be able to collect sufficient amounts of data. German economics minister Altmaier sums it up: “We need data pools in Europe.” But how to pool and share data, while maintaining sovereignty?
Everyone is talking about it, but in praxis it shows: "The subject of AI is completely new territory." Automotive IT asked experts such as Prof. Dr. Chris Schlueter Langdon of T-Systems to explain how to avoid reinventing the wheel.
We asked leading data scientists: How do you spend the next US$1, on more data (quantity) or better data (quality)? And how to measure the quality and quantity of data?
The shift to new mobility services is seen as epic and rapid. In less than two vehicle generations a new service business is estimated to be as big as the auto business.
Despite big investments in Data scientists, expensive IT infrastructure and tools, AI seems to be stuck in first gear. What's often missing is the right management approach - and the right recipe to orchestrate all the new ingredients ...
Big Data is promised to be the next big business. Yet, today, most companies don’t even know how big ‘big’ is, how to size data quantities properly. No surprise that profit is missing. Start measuring!
Digitizing the production line of a Hidden Champion in 100 days? Learn more about how a Telekom Team "walked the talk", used connected sensors and Data Analytics to uncover hidden production issues and improve quality.
If “Time is Money”, then data analytics today is a disaster. Because at least 80% of the time budget of a data analytics project is spent on data preparation, not with analytics and results.