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Ever wondered why we are missing out on getting from point A to point B more quickly in urban areas, such as with intermodal travel? Learn how the Telekom Data Intelligence Hub (DIH) team is using a next-generation European standards-based data sharing and exchange technology referred to as dataspace to speed up personal travel.

We are happy and excited to announce the partnership between T-Systems and sovity (link), a spin-off of the Fraunhofer ISST which provides technology to enable data sovereignty. Together we are taking a step further towards the future of data economy, the secure and controlled exchange of data between companies based on Gaia-X and IDS standards.

We help companies put their data analytics and artificial intelligence (AI) on the right data platform so that data is under control, available, usable, reliable, and secure – all as a managed service in the cloud.

The FAZ has received a new draft law for the sovereign handling and exchange of industrial data within the EU (“Data Governance Act”, link to FAZ article).

Today, data is broken. If “time is money” (Franklin, 1749), then data analytics is a disaster because more than 80% of the time budget of a data analytics project is spent with data processing and refinement – not with results (see “Data is broken,” link). Figure 1 shows a metaphorical example of the problem: At an executive-level “data” tends to be thought of as a product that can be grabbed off the shelf, like bottled water. However, for a data scientist it more like a puddle of water, raw water. Nobody would drink from a puddle. The water would have to be “treated,” analyzed for harmful ingredients and nutrients, labeled and bottled to an exact quantity. This is not cheap. The magnitude of the price difference between raw and bottled water speaks for itself. The price of one liter of branded, bottled water at retail, buys one thousand liters of raw water in Berlin. These numbers make it crystal clear how much value is created from raw to bottled water. The gist of our analogy is this: Data needs refinement and in order to economize on the process it takes – no surprise – a factory. We use factories for everything else. Henry Ford invented the modern factory and with it, automotive as an industry. His factory turned auto-making from a hand-made affair to mass production through automation (Womak et al. 1990). Now we need data factories to stop wasting analytics time on data, to make data analytics scalable.

Politicians, business leaders, economists … Everyone speaks about the platform economy. The pioneers of this development, the American companies Amazon, Google, and Microsoft, were the first incorporated companies ever to break the US$ 1 trillion valuation barriers. The key element of any platform is data: “Data can be used to create a digital image (digital twin) of people and their environment. However, this inherits the risk of losing sovereignty over one’s own data” (BMBF, link). What could a win-win situation for data value creation with data sovereignty look like?

T-Systems has been the leading Information and Communications (ICT) provider for the Automotive sector in Germany in 2020 according to AutomotiveIT. In fact, T-Systems has been a leader for more than 10 years.

Boost your data analytics efforts – join the “data sandbox.” In data analytics today, more than 80% of the time budget is spent on data processing alone. Join the “data sandbox” to create more results faster by benefiting from (a) experiments with complementary data types and (b) better data.

Today, data sharing and data pools are a source of competitive advantage in digital business. German Federal Minister Altmaier recently advocated European data pools to ensure the competitiveness of companies in Europe, particularly small and medium-sized enterprises.

Since 2015 once every year Europe’s top data scientists and data experts from industry make its pilgrimage to its most important gathering, the Data Native Conference in Berlin. This place is special: It’s not an ivory tower event, limited to academics; it’s an event where both scientists and industry experts mingle, brainstorm, code … creating the next big trend. It is also hosted in a special location: The Berlin Kühlhaus (link), build in 1901 as Europe’s largest “fridge” and located near the old Anhalter Bahnhof at Gleisdreieck (link) just south of the famous Potsdam Plaza.

Any prudent investor will carefully weigh investment options. In data science, data is an important ingredient and any prudent data scientist would have to decide on data. So, we asked leading data scientists: How do you spend the next US$1, on more data (quantity) or better data (quality)?

Data monetization is promised to be the next big thing. Analysts and consultants are promising hundreds of billions in revenue (e.g., McKinsey 2016). Her excellence the German Chancellor, Angela Merkel, is addressing the downside, sternly warning German industry to catch up: “If we let this element of value creation be taken out of our hands, then it will be a rude awakening for Germany as an industrial country” (Merkel 2019, link, at 13:17).