Economy

This video blog post serves as a test item to evaluate the integration of multimedia within data-driven publishing workflows. It demonstrates how short video content can be embedded into a standard blog layout to enhance user engagement and content flexibility. This item does not reflect real data or represent an official publication.

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.