Data analytics is the next frontier in accounting. While data analytics can be simple, today the term is most often used to describe the analysis of large volumes of data and/or high-velocity data, which presents unique computational and data-handling challenges. Certified public accountants (CPAs) are constantly using data analytics in daily tasks. There are four types of data analytics: descriptive analytics (Whats happening?), diagnostic analytics (Why did it happen?), predictive analytics (Whats going to happen?), and prescriptive analytics (What should happen?). Descriptive analytics includes the categorization and classification of information. Accurate reporting with large quantities of data is a hallmark of solid accounting practices. Diagnostic analytics monitors changes in data. Accountants regularly analyze variances and calculate historical performance as an indicator of future performance. Predictive analytics assesses the likelihood of future outcomes. Accountants are instrumental in building forecasts and identifying patterns that shape those forecasts. Prescriptive analytics is used to create tangible actions and critical business decisions. Accountants use these forecasts to make recommendations for future growth opportunities. Data analytics offers challenges and opportunities for CPAs. The challenges include obtaining the skills needed to initiate and support data analytics activities, as well as altering the present audit model to include appropriate audit analytics techniques. Opportunities include a technology-rich audit model and the ability to provide data analytics expertise to clients. With the mastery of data analytics, businesses can generate a higher profit margin and gain meaningful competitive advantages.

Describe the different types of analytics and how they can be utilized in the accounting field.