4x Faster Reimbursement Validation
Our team streamlined the reimbursement process and utilized various functionalities of the RPA tool to drastically decrease the processing time and reduce the probability for errors.
4x
faster data processing
Ease
of accessibility and collaboration
High
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.
Client
One of the largest automotive groups in Europe
Solution
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.
Benefits
- 4x faster data processing
- Ease of accessibility and collaboration
- 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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