University of Michigan

Measuring Total Data Quality

This course is part of Total Data Quality Specialization

Taught in English

Brady T. West
James Wagner
Jinseok Kim

Instructors: Brady T. West

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Course

Gain insight into a topic and learn the fundamentals

Beginner level
No prior experience required
9 hours (approximately)
Flexible schedule
Learn at your own pace

What you'll learn

  • Learn metrics for evaluating Total Data Quality.

  • Create a quality concept map of TDQ from a particular application or data source.

  • Identify relevant software and related tools for computing the various metrics.

Details to know

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Assessments

7 quizzes

Course

Gain insight into a topic and learn the fundamentals

Beginner level
No prior experience required
9 hours (approximately)
Flexible schedule
Learn at your own pace

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Build your subject-matter expertise

This course is part of the Total Data Quality Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate
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There are 4 modules in this course

Welcome to Measuring Total Data Quality! This is the second course in the Total Data Quality Specialization. After reviewing the Course 2 syllabus and completing the course pre-survey, you’ll learn how to measure validity for designed and gathered data through a series of video lectures, examples, and readings. You’ll then take a short quiz on interpreting validity metrics. Then, you’ll complete a module on data origin, where you’ll learn about measuring data origin quality for designed and gathered data in a series of video lectures and case studies. Week 1 will conclude with a quiz on interpreting data origin quality metrics.

What's included

9 videos6 readings2 quizzes

Welcome to Week 2 of Measuring Total Data Quality! We’ll begin the week by discussing how to measure processing data quality for designed and gathered data. We’ll include examples of measuring process data quality for each form of data and conclude the module with a quiz on interpreting processing metrics. In the second half of Week 2, we’ll discuss measuring data access quality for designed and gathered data through video lectures, an example, and a case study, and conclude the week with a quiz on interpreting access metrics.

What's included

8 videos2 readings2 quizzes

This week, we’ll learn how to measure data source quality and data missingness. We’ll begin Week 3 with a video lecture on measuring data source quality for designed data. Then, we’ll work through an example of computing data source metrics with real data and code. We’ll then learn how to measure data source quality for gathered data and see an example of computer data source quality metrics with real data and code. You’ll then take a short quiz on interpreting data source quality metrics and move on to the Data Missingness unit. We’ll learn how to measure threats to data source quality for designed and gathered data and work through examples for each form of data. Week 3 will conclude with a quiz on interpreting data missingness metrics.

What's included

8 videos3 readings2 quizzes

We’ll be wrapping up Measuring Total Data Quality this week by learning how to measure the quality of data analysis. We’ll learn how to measure the quality of data analysis for designed and gathered data and work through examples of each type of data. We recommend that you complete two readings before you complete the lecture on measuring the quality of analysis for gathered data. We will conclude the week with a quiz on examining quality metrics and interpreting output, as well as references for the Measuring Total Data Quality course and a course post-survey.

What's included

4 videos6 readings1 quiz

Instructors

Brady T. West
University of Michigan
6 Courses150,424 learners

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