Magneti Marelli

Customer Case Study

Magneti Marelli

Magneti Marelli designs and produces a vast range of systems and components for the automotive sector. Through a process of continuous innovation, it develops advanced systems and solutions that contribute to the evolution of safe and sustainable mobility.

Industry

Automotive

Vertical Use Case

Improve manufacturing efficiencies – Leveraging machine learning and AI to improve all aspects of manufacturing such as reducing product defects, predicting outages, improving production speed, and more.

Technical Use Case

  • Data Ingest and ETL
  • Machine Learning

The Challenges

  • A bootstrapped team of data scientists struggled to collaborate and work effectively together.
  • HIghly complex to build necessary infrastructure to do their job. Spent too much time on DevOps to integrate systems such as PowerBI.
  • Massive data – needed to train models against 10+ years of data which was complex and costly to manage.

The Solution

Databricks provides Magneti Marelli with a unified analytics platform that simplifies infrastructure operations and accelerates their ability to leverage machine learning to solve their manufacturing challenges. This is empowering them to analyze the data in new ways that was previously impossible.

  • Automated cluster management simplifies the provisioning of clusters, reducing time spent on DevOps work so engineers and data scientists can spend more time on high valued tasks.
  • Interactive workspace allows data scientists to share data and insights in notebooks, fostering an environment of transparency and collaboration.
  • Expert Apache Spark support from that helped them onboard and be productive very quickly.

The Results

  • Accelerate time-to-value and improve operational efficiencies within the manufacturing plant.
  • Lower the cost for a new manufacturing line by 90%.
  • 12x increase in return on investment in in a matter of two years, creating potential operational savings of millions of dollars.

Databricks helps make very complex operations very simple. It is a game changer from a time-to-market perspective.

Andrea Condorelli, Head of Data Science at Magneti Marelli