University of Michigan
Design Strategies for Maximizing Total Data Quality
University of Michigan

Design Strategies for Maximizing 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 about design tools and techniques for maximizing TDQ.

  • Identify aspects of the data generating/gathering process that impact TDQ.

  • Understand TDQ maximization strategies that can be applied when gathering designed and found/organic data.

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 Design Strategies for Maximizing Total Data Quality! This is the third and final course in the Total Data Quality Specialization. After viewing a short welcome video, reviewing the course syllabus, and taking a course pre-survey, we’ll begin the course by exploring the topic of validity. You’ll learn how to maximize validity for both designed and gathered data through a series of video lectures, readings, and case studies. We’ll conclude our exploration of validity with a quiz on design strategies for maximizing validity. The second half of Week 1 will focus on data origin. You’ll learn how to maximize data origin quality for designed and gathered data through a series of lectures, examples, and case studies. Week 1 will conclude with a quiz on design strategies for maximizing data origin quality.

What's included

9 videos4 readings2 quizzes

In Week 2, we’ll learn how to optimize data processing quality. We’ll begin the week with video lectures on how to maximize processing quality for designed and gathered data, along with an example for each type of data. We’ll conclude our discussion of processing with a quiz on design strategies for maximizing processing quality. Then, we’ll learn how to maximize data access quality for designed and gathered data while exploring each type of data through video examples and readings. Week 2 will conclude with a short quiz on strategies for maximizing access quality.

What's included

7 videos2 readings2 quizzes

This week, we’ll learn how to optimize the quality of a data source and minimize missing data rates. First, we’ll explore how to maximize data source quality for designed and gathered data. We’ll mix in a series of examples, readings, and case studies throughout our data source unit and conclude this unit with a quiz on strategies for maximizing source quality. Then, we’ll move on to a discussion of data missingness. We’ll learn how to minimize data missingness for designed and gathered data through a series of video lectures and examples. Week 3 will conclude with a short quiz on strategies for minimizing data missingness.

What's included

8 videos3 readings2 quizzes

Welcome to the final week of Design Strategies for Maximizing Total Data Quality and the Total Data Quality specialization! We’ll wrap up the series by learning how to optimize data analysis quality for both designed and gathered data. This exploration will include a series of video lectures and case studies. After you take a quiz on how to maximize data analysis quality, you’ll work on a peer review assignment that asks you to review a study of Wordle performance. The week will conclude with a specialization recap video and a course and specialization post-survey.

What's included

4 videos3 readings1 quiz1 peer review

Instructors

Brady T. West
University of Michigan
6 Courses151,639 learners

Offered by

Recommended if you're interested in Data Analysis

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