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School of Computing · ANU College of Systems and Society
In 2023, this course is on campus with remote adjustments only for participants with unavoidable travel restrictions/visa delays. 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. Other Information You should be enrolled in the Master of Applied Data Analytics, the Graduate Diploma of Applied Data Analytics, or the Graduate Certificate of Data Engineering to undertake this blended intensive course. Note: Non-MADAN, DADAN or GCDE students wanting to enrol are required to seek approval from their Program Convener.
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