The data warehouse architecture entailed importing all data into an OLAP database, calculating and speculating on a “Risk Profile” with human intervention, and then loading it into the ultimate master database.
The data warehouse architecture entailed importing all data into an OLAP database, calculating and speculating on a “Risk Profile” with human intervention, and then loading it into the ultimate master database.
The IZAC analytical framework deployed on the Hadoop architecture revolutionised the building of a customer risk profiling use case with just a 15-node distributed computing setup. The solution utilised the power of Hadoop over Spark computing and machine learning processing frameworks to evolve a system that could auto-profile a customer and calculate a risk score associated with the same.
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