Engineering & Technology

The Crosser platform is taking the SQL simplicity to the next level. By offering a set of pre-built analytics modules and connectors for integration to SQL databases and enabling users to configure various queries for their use cases.

The positive impact of digitalization in asset rich Enterprises is getting more and more recognized globally — reduced costs, improved operational efficiency and greater productivity. New techniques and softwares open up for new and advanced solutions and great technical achievements.

Microsoft Azure connectors are an essential component in the Crosser Module library. Simplifying data storage, file storage and data transfer to Azure IoT Hub and Azure IoT Edge. And select, insert, read and execute SQL statements on MS SQL Server.

Crosser is expanding its library of pre-built connectors for radically simplifying enterprise integration and streaming analytics. The latest release is a set of Snowflake modules for simplifying Enterprise Data Integration.

Crosser and Kafka is a powerful combination of simplicity and functionality for building streaming data pipelines. The combined solution makes it easy to connect and collect data from various sources, and to integrate and send to various systems and services.

The promise of Industry 4.0 sets new expectations for the traditional service bus architecture. The service bus now needs more functionality than before. There is a need for an intelligent integration layer that can run real-time applications and workflows with full data analytics capabilities included.

One of the biggest challenges that Enterprises have in their efforts of digitalization is the fact that they have too many, and complex, data silos. Another is that they have a patch-work of applications that don't follow a common architecture. The promises of Industry 4.0 / Industrial IoT are significant...

In this article published by IoT Business News, Goran Appelquist, CTO at Crosser, provides insight into the five most popular analytics modules being used to create data flows in its platform.

One of Crosser’s aims is to fight complexity with simplicity, and this is evident in the Flow Studio.

Using video cameras as sensors in industrial IoT applications is becoming more and more popular. The reason is of course that it opens up for many interesting applications.

Extracting valuable insights out of data collected from machine sensors can be hard, often requiring analyzing data from many sensors in parallel.
Due to the complexity, machine learning (ML) methods are becoming more and more popular to analyze these datasets.