Elements of Data Processing (COMP20008)

Undergraduate level 2Points: 12.5On Campus (Parkville)

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Overview

Availability
Semester 1
Semester 2
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AIMS

Data processing is fundamental to computing and data science. This subject gives an introduction to various aspects of data processing including database management, representation and analysis of data, information retrieval, visualisation and reporting, and cloud computing. This subject introduces students to the area, with an emphasis on both tools and underlying foundations.

 

INDICATIVE CONTENT

The subject's focus is on the data pipeline, and activities known colloquially as 'data wrangling'. Indicative topics covered include:

  • Capturing data (data ingress)
  • Data representation and storage
  • Cleaning, normalisation and filling in missing data (imputation)
  • Combing multiple sources of data (data integration)
  • Query languages and processing
  • Scripting to support the data pipeline
  • Distributing a database over multiple nodes (sharding), cloud computing file systems
  • Visualisation and presentation

Intended learning outcomes

Communicate effectively about data processing methodologies in oral form

Generic skills

On completion of this subject, students should have developed the following generic skills:

  • An ability to apply fundamental knowledge in reasoning and problem solving
  • An ability to undertake problem identification, formulation and solution
  • The capacity to solve problems, including the collection and evaluation of information
  • The capacity for critical and independent thought and reflection
  • Profound respect for truth and intellectual integrity, and for the ethics of scholarship
  • An expectation of the need to undertake lifelong learning, and the capacity to do so.

Last updated: 9 April 2025

Eligibility and requirements

Prerequisites

One of the following subjects:

Code Name Teaching period Credit Points
COMP10001 Foundations of Computing
Semester 2 (On Campus - Parkville)
Semester 1 (On Campus - Parkville)
 12.5
 
Code Name Teaching period Credit Points
COMP10003 Media Computation
Semester 1 (On Campus - Parkville)
 12.5
 COMP90059

Students who have completed COMP10002 Foundations of Algorithms but neither COMP10001 Foundations of Computing nor COMP10003 Media Computation and who have knowledge of Python are invited to approach the subject coordinator to discuss their possible enrollment into the subject. 

 

Corequisites

None

Non-allowed subjects

INFO20002

Inherent requirements (core participation requirements)

The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.

Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home

Last updated: 9 April 2025

Assessment

Due to the impact of COVID-19, assessment may differ from that published in the Handbook. Students are reminded to check the subject assessment requirements published in the subject outline on the LMS

DescriptionTimingPercentage

One 2-hour end-of-semester examination. Addresses ILO 1 and 2.

  • 2 hours
Hurdle requirement: 20 / 50 in the end-of-semester written examination		During the examination period50%

Project work during semester, applying data processing to datasets, requiring approximately 45-50 hours of work in total, due in approximately week 6 and week 11. Addresses Intended Learning Outcomes, (ILO) 1, 2 and 3.

  • 50 hours (of work required)
Week 1140%

One 5-minute workshop presentation, requiring approximately 10-12 hours of work in total, presented during semester. Addresses ILO 3 and 4.

  • 5 minutes
Hurdle requirement: 20 / 50 in the continuous assessment		Throughout the semester10%

Additional details

 

 

 

Last updated: 9 April 2025

Dates & times

  • Semester 1
    Principal coordinatorPauline Lin
    Mode of deliveryOn Campus (Parkville)
    Contact hours48 hours, comprising of two 1-hour lectures and one 2-hour workshop per week
    Total time commitment170 hours
    Teaching period 2 March 2020 to 7 June 2020
    Last self-enrol date13 March 2020
    Census date30 April 2020
    Last date to withdraw without fail 5 June 2020
    Assessment period ends 3 July 2020

    Semester 1 contact information

    Pauline Lin

    pauline.lin@unimelb.edu.au

  • Semester 2
    Principal coordinatorChris Ewin
    Mode of deliveryOn Campus (Parkville)
    Contact hours48 hours, comprising of two 1-hour lectures and one 2-hour workshop per week
    Total time commitment170 hours
    Teaching period 3 August 2020 to 1 November 2020
    Last self-enrol date14 August 2020
    Census date21 September 2020
    Last date to withdraw without fail16 October 2020
    Assessment period ends27 November 2020

    Semester 2 contact information

    Chris Ewin

    cewin@unimelb.edu.au

Time commitment details

170 hours

Last updated: 9 April 2025

Further information

Last updated: 9 April 2025