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6 Tipps zu IoT Analytics mit der CumulocityIoT Plattform

IoT AnalyticsEigentlich hätte ich gestern auf der buildingIoT Konferenz meinen Talk zu “IoT Analytics – Stream und Batch-Processing” gehalten. Nun ja, es sollte nicht sein. Daher habe ich meine Takeaways hier zusammengefasst.

In IoT Use Cases werden oft Daten verarbeitet. Ab einer gewissen Menge an Daten gibt es einen nicht mehr zu erfüllenden Zielkonflikt zwischen Real-Time-Anforderungen und der Genauigkeit. Dieser lässt sich durch die Lambda-Architektur auflösen und in zwei Layern getrennt erfüllen. In SaaS Plattformen, wie der CumulocityIoT, stehen dazu oft Mittel wie Complex Event Processing (CEP) Engines und REST-Schnittstellen zur Verfügung. Im Falle der CumulocityIoT Plattform läuft die Stream Verarbeitung über die CEP Engine Apama. Es gibt jedoch ein paar Dinge für eine stabile und effektive Verarbeitung zu beachten. Daher hier meine 6 Tipps zu IoT Analytics.

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Review of the Predictive Analytics World Business Conference

Estrel Hotel Berlin
Event Location of Predictive Analytics World Business

The last two days I was at the Predictive Analytics World Business Conference in Berlin. The event happened inside the Estrel Hotel, a nice and good managed location. In the talks of day one, little was in for me. The deep dive tracks were too deep for me. The use case tracks too superficial. At least it looks like presenting companies are using AI/ML in production. This is in contrast to the Industrial Data Science Days in Dortmund earlier this year, where Companies are using AI/ML in scientific PoCs, far from production.

At day two, the talks were much more interesting. My personal highlight was the talk (with the very long title) “Data Science Development Lifecycle – Everyone Talks About It, Nobody Really Knows How to Do It and Everyone Thinks Everyone Else Is Doing It” by Christian Lindenlaub und René Traue. They summarized their learnings from using Scrum and other methods in Machine Learning projects. They showed how to combine different agile methodologies to run successful machine learning + production software projects. Very inspiring for our own projects too.

The following talk “How to Integrate Machine Learning into Serverless Workflows” delivered also some helpful insights for some of Tarent’s current projects.

In the end, a good conference with some points I took home. See you next year? I don’t know yet. We will see.

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