Data Collection and Cleaning

Catalog description

This course focuses on the tools and techniques required for collecting data and preparing them for further analysis. The presence of incorrect and inconsistent data can significantly distort the results of the analysis often negating the potential benefits of information-driven approaches. As a result a variety of research over the last decades has focused on data cleansing: computational procedures to automatically or semi-automatically identify - and, when possible, correct - errors in large data sets. The goal of this course is to explore and discuss different data collection tools and techniques in addition to learning skills for retrieving data from existing databases. To further enforce data quality and reliability this course will cover techniques for error detection and data cleaning on large databases. Students will learn the available tools and techniques for data collection including automated data collection for databases, retrieving data from available databases, data preparation and cleansing techniques, data quality and reliability and finally learn techniques to identify issues in data collection and how to clean the data.