coursemapLoading course
School of Computing · ANU College of Systems and Society
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.
Written and practical assignments
Learning outcomes 1, 2, 3, 4
Oral presentation and report
Learning outcomes 5
Final examination
Learning outcomes 1, 2, 3, 4, 5
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.
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