| dc.description.abstract | With the rapid growth of web platforms, the amount of data generated from user interaction
with websites is enormous. This data is invaluable for businesses seeking to understand their
customers and make informed decisions. Therefore, a robust system for tracking and analyzing
user behavior on the web platform is essential. This thesis proposes a scalable infrastructure design
and implementation for efficient real-time tracking, ingestion, processing, and analysis of user
behavior, utilizing a microservice architecture and big data technologies.
The methodology involves several key steps. First, a software development kit (SDK) is
developed to capture user interactions and publish them to a package manager. Subsequently,
extensive research is conducted to apply big data technologies to construct a scalable and reliable
data layer. The system components, including a data ingestion server and an analytical dashboard,
are then built and integrated with the data layer. Finally, the entire system is deployed to a cloud
platform, and performance tests are conducted to evaluate its effectiveness. | en_US |
