Teaching an Introductory Data Analytics Course Using Microsoft Access®and Excel®

Abstract

Data analytics has been recently adopted by many researchers and professionals working with data in both academic and industry. With the increase in demand for data analysts, there has been a parallel growth in data analytics training programs within companies and educational institutions. In this paper, we introduce the concepts of data analytics and present practical examples using Microsoft Access and Excel. The four types of data analytics (i.e., descriptive, diagnostic, predictive, and prescriptive) are discussed and practical examples are provided. For descriptive analytics, we discuss the data properties and models and present examples of database design and implementation in Microsoft Access. The example for diagnostic analytics involves an ergonomic assessment application in Microsoft Excel to identify the sources of ergonomic risks in work environments. Predictive analytics examples include regression and clustering models implementation in Microsoft Excel. Finally, the prescriptive analytics example involves optimizing the snow removal process in a local city by developing an optimization model and its implementation in Excel. These examples will help students understand data analytics and be able to implement the different data analytics models in Microsoft Access and Excel.