Data Lake & Analytics: Automotive Finance

About the client

Daimler Group provides a comprehensive range of automotive financial services. The products range from leasing and financing options on the financing of dealer firms and the management of commercial fleets to insurance, banking services and innovative mobility services.
Singapore, Global Implementation


Daimler wanted to establish a core data foundation to run scalable advanced analytics aimed to increase top-line business by leveraging customer retention.


Cloud Kinetics Azure team championed a complex regional data migration and change data capture strategy to Azure data factory in real time. This data foundation platform developed in Microsoft Azure was designed to align the business needs to provide intelligent and scalable data models supporting business goals. The solution with Azure Data Lakes to store an unlimited amount of structured, semi-structured or unstructured data from a variety of sources along with Azure data factory gave core callable foundation to the solution.


  • Data Foundation to support future business growth was laid
  • Centralized, cloud-based data hub where business-relevant data is accessible via a
  • comprehensive user interface
  • Scalable analytics with machine learning
  • Self-service to access and manage data sources
  • Comprehensive front-end strategy to make self-service possible.

Success Metrics

  • Built data foundation solution on Azure (Azure Data lake, Data Factory)
  • Scalable advanced analytics saving 80% of time spent earlier
  • Automation on data ingestion process, reducing time spend on data aggregating by 70% .
  • With the entire solution built on Azure, the customer got a centralized, cloud-based data lake foundation to query, join and access incongruent data collected from multiple sources that were initially not supported.
  • Data modernization leads to scalable use case models to be adopted by 42 regions
Tags: Banking & FSI Data Lake & Analytics Microsoft Azure