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Data Quality and Data Engineering
Laseter, Timothy M.; Frazer, Anne; Boatright, Benjamin Technical Note OM-1790 / Published January 31, 2023 / 6 pages. Collection: Darden School of Business
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Product Overview

As companies increasingly rely on data and analytics to make decisions and improve their operations, it becomes clear that data quality can be a major issue. The insights gleaned from data analytics are useful only if the data is of high quality. This note summarizes some common issues that can result in low-quality data and explores the crucial task of data engineering. This note is taught at Darden in the second-year elective, “Digital Operations.” It would also be suitable in a course or module covering data analytics.




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  • Overview

    As companies increasingly rely on data and analytics to make decisions and improve their operations, it becomes clear that data quality can be a major issue. The insights gleaned from data analytics are useful only if the data is of high quality. This note summarizes some common issues that can result in low-quality data and explores the crucial task of data engineering. This note is taught at Darden in the second-year elective, “Digital Operations.” It would also be suitable in a course or module covering data analytics.

  • Learning Objectives