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Big Data, Big Results – Unlocking the Power of Data
The Big Data Service at DB SCHENKER is a powerful platform, operated by the Global Data and AI (GDAI) team built on Microsoft Azure. It serves as the foundation for various data and AI use cases. Let’s dive into the key details.
A Platform Evolving with Business Needs
Established approximately four years ago, the platform initially focused on supporting data scientists with reproducible Machine Learning (ML) trainings, a cornerstone of MLOps. Over time, its capabilities have expanded to handle large-scale big-data analysis and real-time applications, making it an operational solution for diverse data challenges.
Daniel Wallner, Head of Real-Time & MLOps Solutions: “As the foundation of AI use cases at DB SCHENKER, our Big Data Service is pivotal in driving innovation and efficiency. By leveraging vast amounts of data, we can develop intelligent solutions that enhance our operations and deliver superior value to our internal customers.”
Data in Motion: The Azure Data Stack at Work
At the heart of the Big Data Service lies a robust technology built on Azure. Azure Data Lake Gen 2 provides the foundation for storing vast amounts of data, while Azure Data Factory, an ETL (Extract, Transform, Load) solution, orchestrates seamless data movement and transformation. Leveraging Azure Databricks, a collaborative analytics platform for big data and machine learning, teams can collaborate on big data analytics and ML projects, while Azure Machine Learning,empowers data scientists with ML model development and deployment.
Speed and Scale: Automating the Data Pipeline
Efficiency is vital in today’s business environment. The Big Data Service embracesautomation through CI/CD (Continuous Integration/Continuous Deployment) processes, ensuring rapid and reliable deployment of data solutions. Infrastructure as Code (IaC) practices, powered by Terraform, ensure consistent and efficient deployment.
Driving Business Value with Big Data
The Big Data Service supports a diverse range of applications across domains. Advanced predictions, such as shipment event forecasting and estimated arrival calculations, are made possible through sophisticated ML models.Video analysis, enabled by deep neural networks, unlocks new insights from visual data. Additionally, the platform supports demanding, low latency streaming applications essential for operational excellence.
Eva Grieser, Director of Data Management & Architecture, Global Ocean Freight: “BigDaS provides a scalable technical platform for our Ocean Data Cloud, enabling us to implement low-latency data solutions that effectively steer our ocean freight operations.”
The DB SCHENKER Big Data Service is demonstrating the company’s commitment to leveraging cutting-edge technology to optimize logistics and supply chain operations. By combining the power of Azure, automation, and a focus on real-world applications, the platform is driving innovation and delivering tangible business value.
