This module introduces students to data quality assessment methodology which is required prior to analyzing any dataset. Definitions, examples, and exercises are given to provide students an understanding of the steps performed to ensure quality of the data is optimal for analysis.
Students will learn:
the importance of data quality and the key definitions of data quality dimensions
how to obtain access to the required dataset
how to document the work they perform
how to assess the dataset for: * completeness * uniqueness * timeliness * validity * accuracy * consistency
Watch step-by-step instructional videos for each data quality dimension. We walk you through examples for each one so you can see how it's done, hear what our thought process is while we do it and understand why it's important.
Download sample spreadsheets and practice what you just learned in the video. Then take a short quiz to make sure you are on the right track.
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Earn 5.25 CPE Hours
There is a printable Continuing Professional Education (CPE) certificate at the end of the course upon successful completion;
"Why I designed this course"
Alexis C. Bell, MS, CFE, PI
I designed this course as a way to teach data analysis for fraud. In a time when budget cuts cause accountants, investigators, analysts, and auditors to not have access to tools designed for data analytics, the training for those tools, or the labor hours for training time; there had to be an alternative.
This course is the solution for that issue. It is the pre-requisite for a series of courses designed to teach students how to analyze data for fraud by using spreadsheets. Most people have access to a spreadsheet software already. This way they can use a tool they already have to learn what they need to be successful in their role when they have been tasked with data analytics in search of fraud.