Use Cases

The value chain of production in German industry is made up of many different individual segments. For example, a component supplier produces a wide variety of goods, which are then sold to many different machine suppliers. These suppliers manufacture machines that are later used in production. If one imagines the production chains in industry, they resemble a puzzle to whose different parts only individual actors have access and which produces diverse types of data.

In production facilities, all processes are precisely timed, every step must be exact, often in 24/7 operations. If individual machines are down or a production lines fails, then the entire factory gets out of sync, sometimes causing total standstill. The result: production losses, lost sales, repair costs. The goal: to minimize machine downtime – whether through damage or maintenance. This is achieved with artificial intelligence and intelligent evaluation of machine data, in a process that assesses the collected sensor values, control and maintenance data, compares and delivers results to technicians in a targeted manner. Because of the multitude of sensor, control and maintenance data, it is often impossible to consolidate the complex but valuable data and evaluate it in correlation. On top of that, often additional data, e.g. environmental data or data along the supply chain is essential and secure data exchange is required for companies and service technicians.

Room temperature control, access security, maintenance appointments, cleaning work: To manage buildings optimally and keep technical systems in good shape, automated processes are necessary. Secure and easy data exchange is important for facility managers and service technicians. Because different service providers assume different tasks in buildings and use their own information systems and data formats, it is often time-consuming to consolidate the accumulated and required data. Building managers therefore want a broad range of information with uniform interfaces for real estate management and operations. Data sovereignty and ownership play an important role in this.

Something in the air. Municipalities are responsible for making sure there’s clean air on their streets. To do so, air quality is measured at selected locations with the aid of complex and expensive sensors and transmitted to the responsible authorities such as the state, federal government or the EU.

The emergence of data marketplaces is accompanied by the growth of data as the number of collected data is steadily increasing by governments, businesses and websites. Besides data is recognized as an asset and that you can trade it. Data can be bought and sold, creating data marketplaces. But what is a data market place actually? What are the characteristic? These questions are clarified in this blog article.