Faster data processing


of accessibility and collaboration


scalability of resources

Business Case

A leading automotive group was pursuing faster data processing, seamless remote access, and enhanced reporting. A lot of data is generated by the constantly growing number of car IT services. The big data analysis of this data is important to the automotive manufacturer in order to continuously improve the customer experience and achieve faster time-to-market for new features at optimized cost.

The Cloud Migration

Our team migrated the existing Big Data analytics platform entirely to the cloud (AWS). The S3-based data store was optimized according to the world’s best practices. The raw data is ingested from multiple sources in different formats and stored in S3 landing buckets. A Data Lake in parquet format has been created in S3 to speed up the overall data processing. The processed data is loaded into Redshift (AWS column base DB) and/or Postgres.

ETL transformations are applied in the process to give context and greater insight to the data, consequently enhancing Business Intelligence for better decision making. With the ETL processes in place, the data warehouse team re-created interactive analytics dashboards in Tableau and Grafana.

Big data analytics architecture in AWS.


  • 4x faster data processing
  • Ease of accessibility
  • High scalability of resources
  • Processing and Analytics of a larger amount of data at a reduced total cost
  • Cost reduction for storing historical data with AWS S3

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One of the largest automotive groups in the world.

Industry: Automotive

Technology: AWS | Grafana | Tableau

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