Data Lake & Analytics For An
Automotive Company

About the customer

Daimler Group, a automobile manufacturing conglomerate, also provides a comprehensive range of automotive 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.
Industry:
Manufacturing, Finance
Location:
Singapore, Global Implementation

Challenge

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

Need for a core data foundation to run scalable advanced analytics to increase top-line business via customer retention

Need to automate data ingestion process to save time & resources spent on data aggregation

Need for a modern data analytics solution to gain insights from the data collected from multiple sources

Solution

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.

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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

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

The solution built on an Azure data foundation centralized disparate data and automated processes to significantly reduce time spent on data tasks, leading to scalable analytics adoption across 42 regions.

Scalability

Data modernization, with scalable use case models adopted by 42 regions

Speed

- Scalable advanced analytics saving 80% of time spent earlier
- Automation on data ingestion process reduced time spend on data aggregating by 70%

Process Improvement

Centralized, cloud-based data lake foundation to query, join & access incongruent data from multiple, unsupported sources

Tags: AI & ML AI solutions BFSI Data Foundation Data Lake & Analytics Manufacturing & Logistics Microsoft Azure

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