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Abstract

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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Abstract

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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