Identifying Unusual Patterns that Might Indicate Data Integrity Issues

Application Area:
Statistics, Predictive Modeling and Data Mining

Learn to screen data tables for unexpected patterns that might indicate the presence of data integrity issues, from data recording or formatting errors to data falsification. See several case studies in financial, medical, and industrial domains that show how to interactively look for patterns in data tables such as duplicate series of values, linear relationships between columns across groups of rows, properties about the formatted values, and certain distributional properties.

This webinar covers: Explore Patterns utility, establishing conditions for pattern screening and interpreting reports