“What do the numbers tell us?” Show “Let’s dig into the data!” “Can we analyze this in real-time?” It’s very likely that you’ve heard these expressions around the office. Big data. Data analytics. Data science. This is important stuff.
Accountants use data analytics to help businesses uncover valuable insights within their financials, identify process improvements that can increase efficiency, and better manage risk. “Accountants will be increasingly expected to add value to the business decision making within their organizations and for their clients,” comments Associate Professor Wendell Gilland, who teaches Data Analytics for Accountants at UNC Kenan-Flagler Business School. “A strong facility with data analytics gives them the toolset to help strengthen their partnership with business leaders.” Here are a few examples: Auditors, both those working internally and externally, can shift from a sample-based model to employ continuous monitoring where much larger data sets are analyzed and verified. The result: less margin of error resulting in more precise recommendations. Tax accountants use data science to quickly analyze complex taxation questions related to investment scenarios. In turn, investment decisions can be expedited, which allows companies to respond faster to opportunities to beat their competition — and the market — to the punch. Accountants who assist, or act as, investment advisors use big data to find behavioral patterns in consumers and the market. These patterns can help businesses build analytic models that, in turn, help them identify investment opportunities and generate higher profit margins.
To get a better handle on big data, it’s important to understand four key types of data analytics. 1. Descriptive analytics = “What is happening?” 2. Diagnostic analytics = “Why did it happen?” 3. Predictive analytics
= “What’s going to happen?”
4. Prescriptive analytics = “What should happen?”
Accountants have outstanding technical skills. Gilland notes, “Accountants are used to aggregating information to create a picture of an organization that summarizes the details contained in each transaction. Working with descriptive analytics, predictive analytics, and prescriptive analytics comes more easily to people who already possess excellent quantitative skills.” Accountants are natural-born problem solvers. The jump from descriptive and diagnostic analytics to predictive and prescriptive analytics requires that one shift from an organizational mindset to an inquisitive mindset; a shift from stacking and sorting information to figuring out how to use that information to make key business decisions. Accountants are experts at making this jump. Accountants see the larger context and business implications. The true value of data analysis comes not at the point when the data is compiled, but rather when decisions are made using insights derived from the data. To uncover these insights, a data scientist must first understand the business context. Not only do accountants understand this context, they live it.
Build your skills. A Master of Accounting degree from the University of North Carolina will significantly expand your knowledge of data analytics. The topic headlines one of our key courses. And, perhaps more importantly, data analytics is infused into many classes across our curriculum so that you can acquire this critical training in context with many other key topics.
>> Download “What would the accountant
say?” >> Take our Business IQ quiz. Take the Business IQ Test now I’m interested!Complete the fields below. Fields marked with “*” are required. What type of data analysis addresses the question what should be done?Prescriptive analytics helps answer questions about what should be done. By using insights from predictive analytics, data-driven decisions can be made.
What are the four main types of data analytics quizlet?Descriptive Analytics, Diagnostic Analytics, Predictive Analytics, Prescriptive Analytics.
Which basic skills are needed by an analytic minded accountant?Analytical Skills
Accountants must be strong problem-solvers and decision-makers, and must be able to objectively analyze information to identify problems within and challenges facing an organization and its accounting framework, then use an integrated approach to develop effective solutions to address them.
What is the best definition of data analysis quizlet?As described in the text, which of the following best defines the term data analytics? the science of examining raw data, removing excess noise, and organizing it in order to draw conclusions for decision making.
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