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CS5052 Data-Intensive Systems

SCOTCAT credits:15
Academic year(s):2017/8
SCQF Level 11
Planned timetable:To be arranged.

The era of big data is upon us - the volume, velocity and variety of enterprise and scientific data are growing at an exponential rate and will continue to do so for the foreseeable future. This module presents the programming paradigms, algorithmic techniques and design principles for large-scale distributed systems, such as those utilised by companies such as Google, Amazon and Facebook. This module is different in scope from CS4103 (distributed systems) as it focuses primarily on building and utilising large-scale clusters. The module will cover: distributed systems architecture, replication and fault tolerance, storage, coordination, scheduling algorithms, cluster computing, cloud computing, virtualisation, programming models (e.g., MapReduce), stream processing, decentralised systems (e.g., Chord), incentive-based systems (e.g., BitTorrent), and social computing (e.g., crowd sourcing techniques). This module will draw from the latest research in both academia and industry.

Place in programme(s) and relationship to other modules


Optional for Computer Science BSc, Joint Computer Science degrees, Computer Science MSci

UG Pre-requisite(s):(CS2001 or CS2101) and CS2002


Optional for Data-Intensive Analysis MSc Programme. Optional for Computer Communication Systems MSc and all other Postgraduate programmes within the School.

PG Pre-requisite(s):CS5001

Learning and teaching methods and delivery

Weekly contact:2 lectures (x 11 weeks), 1 tutorial (x 5 weeks)
Total module hours:
  • Scheduled learning: 31
  • Guided independent study: 116

Assessment pattern

UG As defined by QAA:
  • Written examinations: 60%
  • Practical examinations: 0%
  • Coursework: 40%
UG As used by St Andrews:2-hour Written Examination - 60%, Coursework = 40%
UG Re-assessment:2-hour Written Examination = 60%, Existing Coursework = 40%
Postgraduate Assessment :2-hour Written Examination = 60%, Coursework = 40%


Module teaching staff: