units

FIT5148

Faculty of Information Technology

print version

6 points, SCA Band 2, 0.125 EFTSL

Postgraduate - Unit

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

Faculty

Information Technology

Unit guides

Offered

Caulfield

  • First semester 2017 (Day)

Monash Online

  • Teaching Period 5 2017 (Online)

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 and processing;
  • introduction to NoSQL and Hadoop stack of technologies.

Outcomes

On successful completion of this unit, students should be able to:

  1. use and explain distributed databases principles;
  2. write and interpret distributed SQL queries;
  3. identify and explain the working of distributed databases and systems;
  4. describe and compare NoSQL technologies;
  5. identify and assess big data concepts and technologies;
  6. use and evaluate applications of the Hadoop stack of technologies;

Assessment

For Monash Online: In-semester assessment: 100%
On-campus: Examination (2 hours): 50%; In-semester assessment: 50%

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

Chief examiner(s)

This unit applies to the following area(s) of study

Advanced data analytics
Data science

Prerequisites

FIT5132 or FIT9132
Student should have an introductory understanding of database concepts and SQL and some programming background.

Prohibitions

FIT5043

Additional information on this unit is available from the faculty at: