• Offered by School of Computing
  • ANU College ANU College of Engineering and Computer Science
  • Classification Advanced
  • Course subject Computer Science
  • Academic career PGRD
  • Course convener
    • EmPr Peter Christen
    • Prof Graham Williams
  • Mode of delivery In Person
  • Co-taught Course
  • Offered in Summer Session 2022
    Second Semester 2022
    See Future Offerings

Note: Non-DADAN/MADAN students wanting to enrol in the non-standard session offerings are required to seek approval from their Program Convener.

Real-world data are commonly messy, distributed, and heterogeneous. This course introduces core concepts of data cleaning and standardisation, and data integration, that are aimed at converting and mapping raw data into other formats that allow more efficient and convenient use and analysis of data. The courses also discusses data quality, management, and storage issues as relevant to data analytics.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

  1. Critically reflect upon different data sources, types, formats, and structures,
  2. Research, justify and apply data cleaning, preprocessing, and standardisation for data analytics,
  3. Apply data integration concepts and techniques to heterogeneous and distributed data,
  4. Interpret, assess and discuss data quality measurements,
  5. Research and justify advanced data wrangling, data integration, and database techniques as relevant to data analytics

Indicative Assessment

  1. Written and practical assignments (40) [LO 1,2,3,4]
  2. Oral presentation and report (20) [LO 5]
  3. Final examination (40) [LO 1,2,3,4,5]

The ANU uses Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.

Workload

The workload for the course is around 130 hours, including reading, the viewing of online course material, participation in face-to-face lectures, practical labs and tutorials, and preparation for assessments.

Inherent Requirements

Not applicable

Requisite and Incompatibility

To enrol in this course you must have completed either COMP7230, COMP6730 or COMP6710; AND COMP7240 or COMP6240. Incompatible with COMP3430. A permission code is needed to take this course in intensive mode.

Prescribed Texts

None

Preliminary Reading

Data Matching - Concepts and Techniques fro Record Linkage, Entity Resolution and Duplicate Detection,
Peter Christen, Springer, 2012.
For more information see: http://users.cecs.anu.edu.au/~christen/data-matching-book-2012.html

Fees

Tuition fees are for the academic year indicated at the top of the page.  

Commonwealth Support (CSP) Students
If you have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). More information about your student contribution amount for each course at Fees

Student Contribution Band:
2
Unit value:
6 units

If you are a domestic graduate coursework student with a Domestic Tuition Fee (DTF) place or international student you will be required to pay course tuition fees (see below). Course tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.

Where there is a unit range displayed for this course, not all unit options below may be available.

Units EFTSL
6.00 0.12500
Domestic fee paying students
Year Fee
2022 $4740
International fee paying students
Year Fee
2022 $6000
Note: Please note that fee information is for current year only.

Offerings, Dates and Class Summary Links

The list of offerings for future years is indicative only.
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.

Summer Session

Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary
Intensive Course
1624 10 Jan 2022 10 Jan 2022 21 Jan 2022 11 Mar 2022 In Person N/A

Second Semester

Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary
7458 25 Jul 2022 01 Aug 2022 31 Aug 2022 28 Oct 2022 In Person N/A

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