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Level Foundation
Course by University of Michigan
Offered by

About

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.

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The "Total Data Quality" specialization offers an in-depth exploration of the Total Data Quality framework, crucial for anyone involved in data science or quantitative analysis. This course, led by experts from Coursera, emphasizes the importance of understanding, evaluating, and maximizing data quality before diving into statistical analysis or applying data science techniques. Targeting data scientists and quantitative analysts, particularly those lacking training in the initial stages of the data science process, this specialization focuses on the critical preliminary steps of scientific investigation. Learners will gain knowledge on generating or gathering data, comprehending data origins, and assessing data quality—ensuring that high standards are met before any analysis begins. This foundation-level course is available through Coursera with two subscription options: Starter and Professional. While the course duration is flexible, the content is designed to equip learners with the skills needed to ensure data integrity, making it an essential component for all data-driven projects.