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The benefits of cloud data analytics and its impact on critical thinking. It highlights the advantages of cloud computing paradigms in extending analytics and facilitating widespread collaboration. The document also emphasizes the reciprocal relationship between data analysis and critical thinking, and how critical thinking is essential at each step of the data analysis process. A case study is presented to demonstrate how critical thinking is needed in diagnostic data analysis.
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Oklahoma State University – Oklahoma City Critical Thinking Lecture Notes Nine PHIL 1313 Fall 2022 Contents: Using data analysis (Clouds Data) to assist data gathering. Lecture Notes Nine In the last ten years, cloud computing paradigms have emerged to extend analytics in exciting new ways. Today, any organization with an urgent need to extract insights from its data can benefit from cloud data analytics due to its inherent speed and scale. Cloud analytic systems can do more than simply provide the infrastructure to store massive amounts of data. Thanks to virtually unlimited compute power analytic results are virtually instantaneous. This makes cloud data analytics ideal for real-time or near real-time endeavors such as a marketing team want to assess the impact of a limited-time offer or promotion through a social media platform. The cloud can also facilitate widespread collaboration. For example, during the early months of 2020 when the COVID-19 virus was spreading fast, cloud data platform capabilities made it easy to create a single source for many applicable COVID data sets that spanned organizations and industries. This made data easily available for investigating public health and business impacts, and provided the huge storage and concurrency required. Due to its iterative nature, data analysis is an ideal setting for developing critical thinking. When we asked Melissa Frazier, a retired vice president for audit and controls for Comfort Systems USA, about this, she said, “Critical thinking is key through each step in the data analysis process. If you don’t do a good job on each step, your result will be flawed or useless.” The relationship also is reciprocal: While analyzing data strengthens critical thinking, critical thinking in turn helps data analysis. Jeff Thomson explains, “Data analysis and critical thinking skills are interdependent. Data analysis requires you to think critically by probing, connecting disparate facts, synthesizing, etc. Likewise, critical thinking is enabled by the ability to think analytically and apply tools to help extract insights and actionable information from data.” But how does critical thinking as we define it merge with diagnostic data analysis? We developed a case study (see “CASE STUDY: Fraudulent Financial Reporting” below) to demonstrate how elements of critical thinking are needed at each step in the data analysis process. The case centers on Emersyn Grace, who was hired to establish an internal audit function for ACJ Company, a wholesaler. As she familiarizes herself with the company’s operations, Emersyn discovers some issues of concern that require her to employ critical thinking skills while further analyzing the company data.
Oklahoma State University – Oklahoma City Critical Thinking Lecture Notes Nine PHIL 1313 Fall 2022 Contents: Using data analysis (Clouds Data) to assist data gathering. Although the case study takes place within an internal audit setting, all accounting, finance, and audit professionals should be able to proficiently perform data analysis procedures like those Emersyn completed. Likewise, Emersyn exhibits critical thinking skills that all accountants, financial managers, and auditors should strive to emulate. Accountants, financial managers, and auditors routinely analyze data as part of their day-to-day responsibilities, but they also need to be alert for and recognize unusual, unanticipated analysis opportunities. Critical thinkers’ curiosity inspires them to watch for potential analysis applications; their creativity enables them to consider what they see from different perspectives; and their skepticism empowers them to sense when what they see just doesn’t seem quite right. Emersyn’s curiosity about ACJ Company—her eagerness to learn—prompted her to analyze its financial statements. Her creativity motivated her to analyze ACJ’s financial position and performance not only from a company-wide perspective but also from a store-by-store perspective. Her skepticism regarding the abnormalities she uncovered in the aggregated account balance data prompted her to extend her analysis by drilling down into the underlying, disaggregated transaction data. After identifying the data analysis opportunity, critical thinkers must plan the analysis. That begins with specifying appropriate objectives. For routine, day-to-day analyses, this is rather straightforward. Specifying the objectives for unforeseen data analysis projects is often driven by skepticism and requires creativity. Critical thinkers instinctively focus their attention on unusual circumstances and events they observe. Then they consider the reasons why the abnormalities may have occurred from various perspectives and set out to investigate them. The causes of unfavorable irregularities in business performance include things like operating inefficiencies, noncompliance with applicable laws and regulations, and fraud. The objective of Emersyn’s premeditated financial statement analysis was motivated by curiosity, not skepticism; she simply wanted to enhance her understanding of ACJ Company’s financial position and performance. Her skepticism kicked in when she uncovered unanticipated abnormalities in specific account balances. Not willing to accept what she had discovered at face value and needing to be convinced that her concerns were warranted, she creatively refocused the objective of her data analysis to assessing the integrity of the underlying transactions.