Thanks for Contacting Crosser

The use of machine learning (ML) models is becoming more and more common in industrial IoT applications, especially for use cases such as anomaly detection and predictive maintenance. ML models are typically trained in the cloud using large stored datasets and iterative processing on powerful servers.

Working with many customer projects over the last years we have learnt that a key success factor is to start with small projects that are easy to implement and finish and then gradually build up to the more advanced/complex use cases. That is, eat the elephant in pieces, don’t try to swallow the whole elephant at once.

A common problem in our industry is data mismatch, data from different sources, to send it to other systems that expects data in another format. These situations are where data transformation and harmonization