Solution Examples
Podcast Episodes
Real-Time Data with Apache Flink: How Ververica and Steadforce Drive IIoT Success
Real-Time over Downtime – Why Apache Flink Is Becoming a Key Technology for Industrial Data Projects Whether it’s predictive maintenance, anomaly detection, or adaptive production control – modern industrial companies face the challenge of not just collecting data, but acting on it in real time. Apache Flink has emerged as the leading tool for stream processing. This episode dives into real-world applications in manufacturing, logistics, and infrastructure – from reducing work-in-progress and monitoring temperature trends to optimizing complex supply chains. You’ll learn how companies gradually extend their existing IT/OT architectures with Flink, what common mistakes to avoid, and why “evolution over revolution” is often the smarter strategy. Also in focus: Why investments in streaming technologies often pay off before the ROI becomes measurable in monetary terms – and how projects can get started efficiently using starter kits, Flink SQL, and the Ververica Cloud. For OT/IT leaders, data architects, and decision-makers in Industrial IoT who want to build scalable, secure, and maintainable streaming use cases.
The journey towards Data Mesh - Exploring the available options
A central topic of the podcast episode is the concept of the data mesh, developed by Zhamak Dehghani. Data Mesh breaks down traditional, monolithic and centralized data structures and looks at data from a new perspective. The concept is based on four principles: Domain ownership, viewing data as a product, promoting self-service and supported governance. Both experts discuss various use cases that are made possible by this type of data integration. One example is the correlation of sales and production data in order to compare customer information and carry out analyses. Another example is the “product carbon footprint”, where data from various sources such as ERP systems and production data must be merged. Finally, Stephan Schiffner and Roland Mackert emphasize the advantages of decentralized data approaches. These enable companies to access their data flexibly and efficiently and use it for business decisions and analyses. Starburst Data’s technology, which is based on the Trino SQL query engine, plays a decisive role in this.
Computer vision and real-time object detection with underwater acoustic modems – What we can learn from dolphins for IoT.
Stephan Schiffner (CTO, Steadforce) develops such digital solutions and platforms with Steadforce. They are scalable, secure and sustainable – like those for underwater experts EvoLogics GmbH. A major challenge in this podcast episode: In water, only a data rate and transmission of a few kilobits per second is possible. Philipp Bannasch (Team Leader Sensor Integration, EvoLogics) talks about how the challenges of data transmission are overcome, how the Steadforce solution makes life easier for users in image evaluation, and how workflows are automated. This podcast episode gets to the heart of how it all works in detail. Rather like to read? No problem: Here you can read the use case. By the way: The use case is transferable and also applicable above water! Who can benefit from it? Companies across industries – automotive, chemicals & pharmaceuticals, metalworking, mining, etc.
