Big Data engine

About the client

The client is one of the leading industrial companies in Europe headquartered in Germany. The company’s primary focus is on the steel production industry.

Our goal

The project’s primary objective was to revolutionize the data analysis and visualization processes within a leading European industrial company specializing in steel production. The aim was to streamline and optimize data handling mechanisms, facilitating more informed decision-making and enhancing overall operational efficiency.

Challenges we faced

The client faced significant challenges in dealing with the exponential growth of data and the limitations of its existing data analysis infrastructure. The company hired the XPG Factor development team to migrate outdated systems to cloud-based platforms and update legacy software.

Implemented solution

The client created the solution for the project to address the challenges faced in handling vast amounts of data and modernizing its data analysis infrastructure. The solution aimed to streamline data processing, enhance visualization capabilities, and facilitate seamless integration with cloud-based platforms. The XPG Factor team was involved in the development and implementation of this solution.

Engine development platform

A robust Engine Development Platform was designed as the leading solution. This platform served as an application framework for assembling and preparing various distributed systems, enabling Level 1 and 2 automation and simulation software.

Advanced-data analysis programs

A suite of advanced data analysis programs was developed using the ENGINE HMI Framework. These programs were tailored specifically for analyzing and visualizing large volumes of data generated within steel production processes. The programs provided intuitive interfaces and powerful analytical tools to extract actionable insights from complex datasets.

Cloud transformation strategy

A comprehensive cloud transformation strategy was implemented to modernize the client’s IT infrastructure. Legacy systems were migrated to advanced cloud-based platforms, ensuring scalability, flexibility, and enhanced data security. This transformation facilitated seamless access to critical data resources from anywhere, at any time, empowering stakeholders with real-time insights and decision-making capabilities.

Integration of OPC UA and RabbitMQ

OPC UA and RabbitMQ were integrated to ensure seamless data communication between various system components. These technologies enabled efficient and reliable data exchange, facilitating smooth interoperability between modules and systems.

Key features

• Scalable Big Data Analysis
  The software can process and analyze large volumes of data, providing comprehensive information for making informed decisions.
• Enhanced Data Visualization
  The platform provided advanced tools for intuitive and comprehensive data visualization, aiding stakeholders in gaining actionable insights from complex data sets.
• Cloud Transformation
  Integrating cloud-based systems facilitated a more flexible and scalable infrastructure, harnessing the benefits of modern cloud technologies while ensuring data security and accessibility.
• Automation and Simulation Software
  The inclusion of Level 1 and 2 automation and simulation software within the framework streamlined various operational processes, enhancing overall efficiency and productivity.

Methodology & transparency

Since the project management was on the client’s side, the development team regularly participated in all calls to discuss the development process. A transparent approach was maintained throughout the project lifecycle, ensuring clear communication and regular progress updates.