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Data analytics for accounting
Data Analytics is changing the business world—data simply surround us! So many data are available to businesses about each of us—how we shop, what we read, what we buy, what music we listen to, where we travel, whom we trust, where we invest our time and money, and so on. Accountants create value by addressing fundamental business and accounting questions using Data Analytics.
All accountants must develop data analytic skills to address the needs of the profession in the future—it is increasingly required of new hires and old hands. Data Analytics for Accounting, 3e recognizes that accountants don’t need to become data scientists—they may never need to build a data repository or do the real hardcore Data Analytics or learn how to program a computer to do machine learning. However, there are seven skills that analytic-minded accountants must have to be prepared for a data-filled world, including:
Developed analytics mindset—know when and how Data Analytics can address business questions.
Data scrubbing and data preparation—comprehend the process needed to clean and prepare the data before analysis.
Data quality—recognize what is meant by data quality, be it completeness, reliability, or validity.
Descriptive data analysis—perform basic analysis to understand the quality of the underlying data and their ability to address the business question.
Data analysis through data manipulation—demonstrate ability to sort, rearrange, merge, and reconfigure data in a manner that allows enhanced analysis. This may include diagnostic, predictive, or prescriptive analytics to appropriately analyze the data.
Statistical data analysis competency—identify and implement an approach that will use statistical data analysis to draw conclusions and make recommendations on a timely basis.
Data visualization and data reporting—report results of analysis in an accessible way to each varied decision maker and his or her specific needs.
Consistent with these skills, it’s important to recognize that Data Analytics is an iterative process. The process begins by identifying business questions that can be addressed with data, extracting and testing the data, refining our testing, and finally, communicating those findings to management. Data Analytics for Accounting, 3e describes this process by relying on an established Data Analytics model called the IMPACT cycle:1
Identify the questions.
Master the data.
Perform test plan.
Address and refine results.
Communicate insights.
Track outcomes.
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Adapted from Win with Advanced Business Analytics: Creating Business Value from Your Data, by Jean Paul Isson and Jesse S. Harriott.
The IMPACT cycle is described in the first four chapters, and then the process is illustrated in auditing, managerial accounting, financial accounting, and taxes in Chapters 5 through 9. In response to instructor feedback, Data Analytics for Accounting, 3e now also includes two new project chapters, giving students a chance to practice the full IMPACT model with multiple labs that build on one another.
Data Analytics for Accounting, 3e emphasizes hands-on practice with real-world data. Students are provided with hands-on instruction (e.g., click-by-click instructions, screenshots, etc.) on datasets within the chapter; within the end-of-chapter materials; and in the labs at the end of each chapter. Throughout the text, students identify questions, extract and download data, perform testing, and then communicate the results of that testing.
The use of real-world data is highlighted by using data from Avalara, LendingClub, College Scorecard, Dillard’s, the State of Oklahoma, as well as other data from our labs. In particular, we emphasize the rich data from Dillard’s sales transactions that we use in more than 15 of the labs throughout the text (including Chapter 11).
Data Analytics for Accounting, 3e also emphasizes the various data analysis tools students will use throughout the rest of their career around two tracks—the Microsoft track (Excel, Power BI) and a Tableau track (Tableau Prep and Tableau Desktop—available with free student license). Using multiple tools allows students to learn which tool is best suited for the necessary data analysis, data visualization, and communication of the insights gained—for example, which tool is easiest for internal controls testing, which is best for analysis or querying (using SQL) big datasets, which is best for data visualizations, and so on.
https://bookshelf.vitalsource.com/reader/books/9781265631529
Ketersediaan
| Call Number | Location | Available |
|---|---|---|
| 657 RIC d | PSB lt.1 - B. Wajib | 1 |
| Penerbit | New York Mc Graw Hill., 2023 |
|---|---|
| Edisi | 3 |
| Subjek | Data Analytics - Accounting |
| ISBN/ISSN | 9781265094454 |
| Klasifikasi | 657 |
| Deskripsi Fisik | xxi, 593 p. : ill. ; 26 cm. |
| Info Detail Spesifik | - |
| Other Version/Related | Tidak tersedia versi lain |
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