Bachelor Thesis Vladimir Elvov

Design of Big Data Reference Architectures for Use Cases in the Insurance Sector

Abstract

In spite of Big Data and the corresponding technologies being already widespread, many Big Data projects do fail or do not deliver the promised results. This is also the case in the insurance sector. One reason is the approach to the respective projects: It doesn’t take into account or analyse the business value of a specific Big Data Use Case or its implementation complexity and feasibility. 
This thesis uses a different approach by analysing the business aspects of Use Cases in the insurance sector at the beginning. First, a number of possible Use Cases in insurance is derived from a literature study. Then these Use Cases are evaluated in expert interviews in order to find out, which ones do have the highest potential. During these interviews, requirements for operationalising these Use Cases are already elicited.
Eventually, based on these requirements and a comparison of existing Reference Architectures for Big Data in common, a new Reference Architecture is designed for Big Data in insurance. The final goal is to use this Reference Architecture as a blueprint for deriving components in order to implement Big Data Use Cases in insurance.

Research Questions:

1. What are possible Big Data Use Cases in the insurance sector and which ones do have the highest potential?

2. Which requirements have to be fulfilled in order to implement these Use Cases?

3. What can a possible Big Data Reference Architecture for insurance look like in order to operationalise the Use Cases from RQ1?