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
Our client Cariad, a Vokswagen Group member, 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.
Cariad
a Volkswagen Group member
Solution
Our team migrated the existing Big Data Analytics platform entirely to the Cloud (AWS). The Amazon 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 Amazon S3 landing buckets. A Data Lake in parquet format has been created to speed up the overall data processing. The processed data is loaded into Amazon Redshift (AWS Data Warehousing Solution) and Postgres.
ETL transformations are applied in AWS Glue 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. In addition, Amazon SageMaker is used to train machine learning models for further insights.
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 Amazon S3
Learn Our Solution From CARIAD
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