Research Associate Professor
6 Learning Experiences
Total Data Quality
What You'll Learn
- Explore the Total Data Quality framework
- Understand on the initial steps of data science, emphasizing data collection, data source evaluation, and techniques for ensuring high-quality data
- Learn how to integrate data quality assessments as a critical component in all your projects
3-Course Series
30 hours
10 hours per course (approx.)
Shareable Certificate
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About Total Data Quality
This specialization aims to explore the Total Data Quality framework in depth and provide learners with more information about the detailed evaluation of total data quality that needs to happen prior to data analysis. The goal is for learners to incorporate evaluations of data quality into their process as a critical component for all projects. We sincerely hope to disseminate knowledge about total data quality to all learners, such as data scientists and quantitative analysts, who have not had sufficient training in the initial steps of the data science process that focus on data collection and evaluation of data quality. We feel that extensive knowledge of data science techniques and statistical analysis procedures will not help a quantitative research study if the data collected/gathered are not of sufficiently high quality.
This specialization will focus on the essential first steps in any type of scientific investigation using data: either generating or gathering data, understanding where the data come from, evaluating the quality of the data, and taking steps to maximize the quality of the data prior to performing any kind of statistical analysis or applying data science techniques to answer research questions. Given this focus, there will be little material on the analysis of data, which is covered in myriad existing Coursera specializations. The primary focus of this specialization will be on understanding and maximizing data quality prior to analysis.
Skills You'll Gain
- Data Quality
- Data Validation
- Data Classification
- Data Wrangling
- Data Analysis
- Data Quality Assessment
What You'll Earn
- Certificate of Completion
- Certificates of completion acknowledge knowledge acquired upon completion of a non-credit course or program.
Research Professor
3 Learning Experiences
Research Assistant Professor
3 Learning Experiences
Adjunct Research Professor
3 Learning Experiences
Course content developed by U-M faculty and managed by the university. Faculty titles and affiliations are updated periodically.
Beginner Level
No prior experience required.
Series Video
3 Courses in this series
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Free U-M Access CourseThe Total Data Quality Framework
Learn how to assess and improve data quality before analysis using the Total Data Quality framework.
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Free U-M Access CourseMeasuring Total Data Quality
Learn how to evaluate and measure data quality at each stage of the data lifecycle using metrics, tools, and real-world applications.
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Free U-M Access CourseDesign Strategies for Maximizing Total Data Quality
Learn to ensure high data quality during collection and design processes to improve the integrity of research and analytics.
