A key performance indicator (KPI) system is a system that tracks specific key objectives for a business organization and measures its performance. This can help an organization to get a better overview of their business, what metrics are the most important, how to improve their business, and make better decisions to move forward. Especially for travel companies, KPI systems are of critical importance, through it they can better understand where they should set their focus in order to reach more customers and make customers more satisfied and see if the business is achieving their wanted performance. The biggest problem in implementing of KPI System from a computer science perspective is how to work with big data sets. To collect and analyze big complex data that come from different storages and in real-time is a challenge. In this thesis, we will show the way to overcome those challenges and implement KPI System for a Business Travel Company called Tourist Mobile in Innsbruck. The main work will be focused on how to collect and analyze the big data, which comes from multiple different sources, is multitenant, and must be accessed anonymously. Data should be processed, served to API business logic of the system which will then work on it as it is specified in requirements, and served to the frontend to end-user. This approach should be accomplished through microservice architecture with each microservice having its own assignments and using different KPI algorithms.