Advanced Data Systems
In this course, you will both learn state-of-the-art techniques that power state-of-the-art data-intensive applications and systems running on modern hardware and get to apply these techniques on a modern data-intensive system.
To transform the sheer amount of complex data into timely discoveries that influence the society, data-intensive systems (including database systems and machine learning platforms) must utilize the full processing power offered by modern processor and storage technologies.
In this course, you will learn the state-of-the-art techniques for data management and processing on modern hardware (multicores, hardware accelerators, microsecond-scale storage, and 100 GBE).
In parallel, you will apply
some of these techniques on widely-used open-source data-intensive systems.
As a result, you will get hands-on experience with how to design, implement, and evaluate new components of an open-source data-intensive system.
Computer Systems Performance class.
Intended learning outcomes
After the course, the student should be able to:
- Analyze the functional and performance requirements of a data-intensive system (e.g., database system or machine learning platform)
- Navigate the codebase of complex production-grade open-source software
- Design and implement components in the context of a production-grade data system
- * Evaluate the performance characteristics of a software system
- Reflect upon the evolution of the hardware (processors, storage, networks) and its impact on the landscape of data-intensive systems and applications
- Reflect upon research papers published by others and present research work to a broad technical audience
Ordinary examExam type:
D: Submission of written work with following oral, External (7-point scale)
D22: Submission with following oral exam supplemented by the submission.