Engineering & Technology

Explore how Crosser’s Hybrid Low-Code solution simplifies data transformation for ETL, ELT, and Reverse ETL pipelines for enterprise data.

This article explains how to use metadata driven stream processing for performing calculations, validations and comparisons in your real-time data flows and pipelines.

The term data pipeline has become very popular in today's data-driven landscape. In this article, we will delve into the crucial topic of ensuring data quality within event-driven data pipelines. 

Explore how and when you can use Python for advanced analytics when building data pipelines and Flows within the Crosser Solution. There are currently over 200 modules in the Crosser Module Library that you can combine with your Python functionality.

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.