units

FIT5148

Faculty of Information Technology

18 September 2017 22 November 2024
Monash University

Postgraduate - Unit

This unit entry is for students who completed this unit in 2015 only. For students planning to study the unit, please refer to the unit indexes in the the current edition of the Handbook. If you have any queries contact the managing faculty for your course or area of study.

print version

6 points, SCA Band 2, 0.125 EFTSL

Refer to the specific census and withdrawal dates for the semester(s) in which this unit is offered.

LevelPostgraduate
FacultyFaculty of Information Technology
OfferedNot offered in 2015

Notes

Monash Online offerings are only available to students enrolled in the Graduate Diploma in Data ScienceGraduate Diploma in Data Science (http://online.monash.edu/course/graduate-diploma-data-science/?Access_Code=MON-GDDS-SEO2&utm_source=seo2&utm_medium=referral&utm_campaign=MON-GDDS-SEO2) via Monash Online.

Synopsis

Data engineering is about developing the software (and hardware) infrastructure to support data science. This unit introduces software tools and techniques for data engineering, but not hardware. It will cover:

  • traditional methods of data processing such as RDBMS, SQL for structured data;
  • introduction to distributed databases;
  • structured vs. unstructured data;
  • introduction to big data and its handling;
  • introduction to NoSQL and Hadoop stack of technologies;
  • introduction to building a data mining framework for big data.

Outcomes

On successful completion of this unit a student should be able to:

  • use and explain advanced databases concepts;
  • write and interpret advanced SQL queries;
  • identify and explain the working of distributed databases and systems;
  • explain use of unstructured data and NoSQL technologies;
  • evaluate applications of the Hadoop stack of technologies;
  • demonstrate how to handle big data;
  • implement data mining and machine learning solutions on a prototyping scale.

Assessment

In-semester assessment: 100%

Workload requirements

Minimum total expected workload equals 144 hours per semester comprising:

(a.) Contact hours for on-campus students:

  • Two hours/week lectures
  • Two hours/week laboratories

(b.) Contact hours for Monash Online students:

  • Two hours/week online group sessions.
  • Online students generally do not attend lecture, tutorial and laboratory sessions, however should plan to spend equivalent time working through resources and participating in discussions.

(c.) Additional requirements (all students):

  • A minimum of 8 hours per week of personal study (22 hours per week for Monash Online students) for completing lab/tutorial activities, assignments, private study and revision, and for online students, participating in discussions.

See also Unit timetable information

Prerequisites

FIT5132 or FIT9132