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Course Description

The data privacy journey begins with assessing the privacy of your customer-level data. To make this assessment, you must first identify the types of customer-level data you have and how identifiable and sensitive they are. One way of doing this is by looking at the uniqueness of customer-level data, which indicates the level to which individuals are able to be identified if the data set is breached. In this lesson, you will explore privacy metrics related to the uniqueness of a data set; in particular, you will examine k-anonymity. You will also consider the impact of your data set's sample size as well as the impact of population size on k-anonymity.

Benefits to the Learner

  • Explore privacy metrics such as k-anonymity
  • Consider the impact of sample size on k-anonymity
  • Examine the unique privacy metrics of a data set
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Type
self-paced (non-instructor led)
Dates
Feb 23, 2021 to Dec 31, 2030
Total Number of Hours
1.0
Course Fee(s)
Regular Price $0.00
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