Customer Case Study


Zalando is a German electronic commerce company based in Berlin. The company maintains a cross-platform online store that sells shoes, fashion and beauty items.

Vertical Use Case

Recommendation Engine – Create a personalized shopping experience that drives engagement, conversion and customer lifetime value.

Technical Use Case

  • Data Ingest and ETL
  • Machine Learning
  • Deep Learning

The Challenges

  • Siloed team that use a myriad of technologies creates operational complexity and hinders cross-team collaboration and productivity.
  • Team spent massive amounts of time on DevOps to integrate these technologies, hindering their ability to deliver to the business in a timely manner.
  • Lack of deep Apache Spark expertise acted as a roadblock to fully leveraging its libraries and capabilities.
  • GDPR compliance – ensuring that their customer data is safe.

The Solution

Databricks provides Zalando with a unified analytics platform that simplifies infrastructure operations and accelerates their ability to leverage machine learning to solve their manufacturing challenges.

  • Fully managed platform allows Zalando to do data science faster, better, and cheaper.
  • Automated cluster management allows for easy provisioning of clusters which reducing operational costs due to features like auto-scaling and Spot Instances.
  • Databricks Delta provides the level of data reliability and governance needed to adhere to strict GDPR compliance standards.
  • Support for multiple programming languages allowed data engineers, analysts, and data scientists to access and leverage the data to drive insights and build models.
  • Integrate with TensorFlow to build and train deep learning models.