IS 537 AO1 - T & P of Data Cleaning - Theory & Prac of Data Cleaning

Description:

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. Course Information: Same as CS 513. 4 graduate hours. No professional credit.

Special Instructions:

This course meets with IS 537 AO. Graduate student questions may be sent to ischool-advising@illinois.edu

Option 1

Number of Required Visit(s): 0

Course Level: Graduate

Credit: 4

Term(s): Fall