4x Faster Data Processing with AWS Cloud Analytics Platform
A leading automotive company was pursuing faster data processing, seamless remote access, enhanced reporting, and better customer experience facilitated by faster time to market for new features at optimized cost.
Faster data processing
more data at lower costs
resource scalability
Business Case
An automotive company 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 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.
Benefits
- 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
