Reproducible & Distributed Heterogenous Data Landscape (Master Project, Ongoing)
Author
Description
This project has two main objectives. First, it aims to develop an orchestration system capable of deploying a heterogeneous data landscape based on an existing use case. This use case should incorporate real-world data sources, such as sensor-generated data, stream processing mechanisms, and database storage solutions. A potential example is the smart city model Metropol.
The second objective is to identify components that could be replaced with more suitable and efficient multi-model solutions, evaluating their impact using key metrics such as performance, complexity, and maintainability. Depending on time constraints, additional avenues may also be explored, comparing different degrees of multi-model components, leveraging dynamic (materialized) views for stream processing lookups, utilizing database engines for small-scale processing tasks, or adopting cross-model approaches to minimize data egestion requirements.
Start / End Dates
2025/04/16 - 2025/07/16