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.
Additional source review: awaiting review. Published wording is shown below.
Saved requirements encoded for automatic checks. These are prototype interpretations, not ANU decisions or degree-completion checks.
Requisite and Incompatibility
To enrol in this course you must have completed: 6 units of (COMP1110 or COMP1140 or COMP6730 or COMP6710) AND 6 units of (COMP2400 or COMP6240). Incompatible with COMP3430 and COMP8930.
Referenced entries (8)
Links and code mentions retain their original context above. They may describe options, prerequisites or exclusions.
- COMP1110 · 2027 · saved source not linked
- COMP1140 · 2027 · saved source not linked
- COMP6730 · 2027
- COMP6710 · 2027
- COMP2400 · 2027 · saved source not linked
- COMP6240 · 2027
- COMP3430 · 2027 · saved source not linked
- COMP8930 · 2027 · saved source not linked
Learning Outcomes
Upon successful completion, students will have the knowledge and skills to:
Critically reflect upon different data sources, types, formats, and structures,
Research, justify and apply data cleaning, preprocessing, and standardisation for data analytics,
Apply data integration concepts and techniques to heterogeneous and distributed data,
Interpret, assess and discuss data quality measurements,
Research and justify advanced data wrangling, data integration, and database techniques as relevant to data analytics
Published offerings
Future offerings are indicative. Only recognised 2027 sessions with a published class number are offered in the enrolment demo.
| Year | Session | Class number | Class start date | Last day to enrol | Census date | Class end date | Mode Of Delivery | Class Summary |
|---|---|---|---|---|---|---|---|---|
| 2027 | Second Semester | 10380 | 26 Jul 2027 | 02 Aug 2027 | 31 Aug 2027 | 29 Oct 2027 | In Person | N/A |
| 2028 | Second Semester | 11046 | 24 Jul 2028 | 31 Jul 2028 | 31 Aug 2028 | 27 Oct 2028 | In Person | N/A |
Complete offering text
ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage. 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. 2027 2028 Second Semester Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary 10380 26 Jul 2027 02 Aug 2027 31 Aug 2027 29 Oct 2027 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 11046 24 Jul 2028 31 Jul 2028 31 Aug 2028 27 Oct 2028 In Person N/A
Source evidence (2 saved copies)
Matching copies share this record. Their original file locations and checksums are retained.
assets/Courses/Data Science/6000/Data Wrangling/Data Wrangling - ANU.html
Published ANU page · saved page URL
SHA-256: 8e9990de7666bcee59dcbc97cc152ab5ee01e7d1096b77e69a305396384f8c31assets/Courses/Remained/6000/Data Wrangling - 6434/Data Wrangling - ANU.html
Published ANU page · canonical URL in the saved page
SHA-256: 7d3155b75799a0d142d46fdb9a3fc10d3fb2a8d5c310557c3f4467ccc99f70a9