IS 532

Spring 2020 Part of Term 1

Part of Term 1
Jan 21-May 6

Theory & Practice of Data Cleaning

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Credit: 4 hours.

Data cleaning (also: cleansing) is the process of assessing and improving data quality for later analysis and use, and is a crucial part of data curation and analysis. This course identifies data quality issues throughout the data lifecycle, and reviews specific techniques and approaches for checking and improving data quality. Techniques are drawn primarily from the database community, using schema-level and instance-level information, and from different scientific communities, which are developing practical tools for data pre-processing and cleaning.

Same as CS 513. 4 graduate hours. No professional credit.

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IS 532 class schedule data for spring 2020
	CRN	Type	Section	Time	Day	Location	Instructor	Section Details
	67443	Lecture-Discussion	A	5:00PM -7:00PM	R	126 Grad Sch of Lib & Info Science	Cheng, J Ludaescher, B	Part of Term: 1 Date Range: 01/21/20-05/06/20 Section Info: This is a hybrid course that meets with IS 532 AO. Restriction(s): Restricted to Graduate - Urbana-Champaign. Restricted to students in the Information Sciences department.
	67444	Online	AO	5:00PM -7:00PM	R	n.a.	Cheng, J Ludaescher, B	Part of Term: 1 Date Range: 01/21/20-05/06/20 Section Info: This is a hybrid course that meets with IS 532 A. Restriction(s): Restricted to Graduate - Urbana-Champaign. Restricted to students in the Information Sciences department.