Advanced Data Systems (Autumn 2021)

Abstract

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.

Description

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 a production-grade open-source system.

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.

Formal prerequisites

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 exam

Exam type:
D: Submission of written work with following oral, Internal (7-point scale)
Exam variation:
D2G: Submission for groups with following oral exam supplemented by the submission. Shared responsibility for the report.