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.
Some conditions may need additional evidence or clarification. These are prototype interpretations, not ANU decisions or degree-completion checks.
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.
Referenced entries (6)
Links and code mentions retain their original context above. They may describe options, prerequisites or exclusions.
- COMP7230 · 2027 · saved source not linked
- COMP6730 · 2027
- COMP6710 · 2027
- COMP7240 · 2027 · saved source not linked
- COMP6240 · 2027
- COMP3430 · 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
The page explicitly says there are no current offerings. This does not establish permanent discontinuation.
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. There are no current offerings for this course.
Source evidence (1 saved copy)
Matching copies share this record. Their original file locations and checksums are retained.
assets/Courses/Remained/8000/Data Wrangling - 8430/Data Wrangling - ANU.html
Published ANU page · canonical URL in the saved page
SHA-256: e4ff6fe3f4b1ed17edf0d1c839bb810242fd87210e53ab9eedf3150983e28aa1