scholarly journals A Model to Integrate Data Analytics in the Undergraduate Accounting Curriculum.

2020 ◽  
Author(s):  
Hussein Issa ◽  
Amer Qasim ◽  
Ghaleb El Refae ◽  
Alexander J. Sannella
Keyword(s):  
Data Analytics ◽  
Accounting Curriculum ◽  
Integrate Data

A Model to Integrate Data Analytics in the Undergraduate Accounting Curriculum

2020 ◽  
Vol 17 (2) ◽  
pp. 31-44
Author(s):  
Amer Qasim ◽  
Hussein Issa ◽  
Ghaleb A. El Refae ◽  
Alexander J. Sannella
Keyword(s):  
Data Analysis ◽  
Learning Outcomes ◽  
Data Analytics ◽  
Curriculum Integration ◽  
Supplemental Reading ◽  
Credit Hours ◽  
Accounting Curriculum ◽  
Reading Materials ◽  
Accounting Courses ◽  
Integrate Data

ABSTRACT This paper proposes a model to integrate data analytics into current undergraduate accounting curricula across existing courses rather than offering a stand-alone data analytics course. One of the advantages of curriculum integration is that students are introduced to data analysis in a progressive or sequential way. Furthermore, such an approach typically does not require additional credit hours to reflect the changes made to the accounting curriculum to introduce the emerging technologies used in the accounting profession. The model proposes course learning outcomes (CLOs) related to the data analytics applications linked to specific levels of study and accounting courses. In addition, teaching materials including the main textbook, supplemental reading materials, and case studies are mapped across accounting courses. This model is expected to be beneficial for accounting educators and members of curriculum committees when updating an accounting curriculum to include data analytics.

scholarly journals PatchIndex: exploiting approximate constraints in distributed databases

2021 ◽  
Author(s):  
Steffen Kläbe ◽  
Kai-Uwe Sattler ◽  
Stephan Baumann
Keyword(s):  
Data Analytics ◽  
Distributed Databases ◽  
Database Systems ◽  
Optimization Techniques ◽  
Cloud Data ◽  
Database Administrator ◽  
Small Set ◽  
Parallel Index ◽  
Access Data ◽  
Integrate Data

AbstractCloud data warehouse systems lower the barrier to access data analytics. These applications often lack a database administrator and integrate data from various sources, potentially leading to data not satisfying strict constraints. Automatic schema optimization in self-managing databases is difficult in these environments without prior data cleaning steps. In this paper, we focus on constraint discovery as a subtask of schema optimization. Perfect constraints might not exist in these unclean datasets due to a small set of values violating the constraints. Therefore, we introduce the concept of a generic PatchIndex structure, which handles exceptions to given constraints and enables database systems to define these approximate constraints. We apply the concept to the environment of distributed databases, providing parallel index creation approaches and optimization techniques for parallel queries using PatchIndexes. Furthermore, we describe heuristics for automatic discovery of PatchIndex candidate columns and prove the performance benefit of using PatchIndexes in our evaluation.

A Framework and Resources to Create a Data Analytics-Infused Accounting Curriculum

2021 ◽  
Author(s):  
Kevin E Dow ◽  
Norman Jacknis ◽  
Marcia Weidenmier Watson
Keyword(s):  
Critical Thinking ◽  
Diffusion Of Innovation ◽  
Data Analytics ◽  
Thinking Skills ◽  
Critical Thinking Skills ◽  
Accounting Students ◽  
Diffusion Of Innovation Theory ◽  
Fully Integrated ◽  
Accounting Curriculum ◽  
Data Analytic

The technology and Data Analytics developments affecting the accounting profession in turn have a profound effect on accounting curriculum. Accounting programs need fully-integrated accounting curriculum to develop students with strong analytic and critical thinking skills that complement their accounting knowledge. This will meet the profession's expectation that accounting students have expert level skills in both technical accounting knowledge and Data Analytics. This paper provides a framework and the resources for creating a Data Analytics-infused accounting curriculum. Specifically, using the Diffusion of Innovation Theory, we apply the theory's five stages to the infusion of Data Analytics into the accounting curriculum: Knowledge, Persuasion, Decision, Implementation, and Confirmation. We formulate an Analytics Value Cube to guide the use of different analytic techniques as accounting programs integrate. We recommend free tools, questions, and cases for use across the curriculum. While our focus is on accounting programs new to Data Analytics, these resources are also useful to accounting programs and practitioners that wish to expand their data analytic offerings.

Has Excel Become a "Golden Hammer": The Paradox of Data Analytics in SME Clusters

2021 ◽  
Author(s):  
Kimberly Swanson Church ◽  
Jennifer Riley ◽  
Pamela J. Schmidt
Keyword(s):  
Data Analytics ◽  
Survey Study ◽  
Business Sector ◽  
Large Firms ◽  
Curriculum And Pedagogy ◽  
Empirical Survey ◽  
Accounting Curriculum ◽  
Analytic Skills ◽  
The U.S ◽  
New Jobs

Demand for data analysis skills in the accounting profession is well documented and necessarily informs accounting curriculum and pedagogy. This empirical survey study focuses on small and medium-sized entities (SMEs), finding SMEs continue to use Excel spreadsheets extensively for data analytics tasks. SME cluster research suggests different adoption rates for technology between this segment and large firms. Investigating SME demands for skills and abilities of new job entrants differs from the large organizations that served as the original drivers of analytic skills and technology recommendations. Findings in this study suggest SMEs continue performing their leading accounting tasks using Excel spreadsheets, and lag in adoption of data analytics technology. SMEs are a significant business sector comprising 95-99 percent of firms in the U.S. economy, creating 65 percent of new jobs from 2000-2018 (USSBA 2019), and competing with large firms but with fewer resources. These findings will guide educators in SME markets.

scholarly journals From Data to Stochastic Modeling and Decision Making: What Can We Do Better?

2019 ◽  
Vol 36 (06) ◽  
pp. 1940012
Author(s):  
Joost Berkhout ◽  
Bernd Heidergott ◽  
Henry Lam ◽  
Yijie Peng
Keyword(s):  
Decision Making ◽  
Operations Research ◽  
Paradigm Shift ◽  
Data Analytics ◽  
Numerical Experiments ◽  
Input Uncertainty ◽  
The Past ◽  
Integrate Data ◽  
Maintenance Problem ◽  
Model Based Analysis

In the past decades we have witnessed a paradigm-shift from scarcity of data to abundance of data. Big data and data analytics have fundamentally reshaped many areas including operations research. In this paper, we discuss how to integrate data with the model-based analysis in a controlled way. Specifically, we consider techniques to quantify input uncertainty and the decision making under input uncertainty. Numerical experiments demonstrate that different ways in decision making may lead to significantly different outcomes in a maintenance problem.

The strategic transformation of accounting into a learned profession

2020 ◽  
pp. 095042222095431
Author(s):  
Melissa Aldredge ◽  
Courtenay Rogers ◽  
James Smith
Keyword(s):  
Artificial Intelligence ◽  
Higher Education ◽  
Machine Learning ◽  
Data Analytics ◽  
Broad Sense ◽  
Skills Gap ◽  
Accounting Profession ◽  
Current Technology ◽  
Accounting Curriculum ◽  
Strategic Transformation

The skills gap in the accounting profession is not a new issue. More than 30 years of research and studies all point to an ever-increasing disparity between what accountants do and what the mainstream accounting curriculum teaches. Technology and businesses are changing and evolving rapidly, as are the expectations for accountants. Advances in the areas of automation and machine learning, artificial intelligence, data analytics and blockchain are examples of current technology disruptions in the accounting industry. The competencies and skills needed today for the accounting profession in the broad sense are not being taught by most universities. The purpose of this paper is to explore what these competencies and skills are, and why accounting curricula needs a strategic transformation into higher education for a learned profession.

COMBINING DATA ANALYTICS WITH XBRL: THE VIEWDRIVE CASE

2021 ◽  
Author(s):  
Amanuel Fekade Tadesse ◽  
Nishani Vincent
Keyword(s):  
Active Learning ◽  
Real World ◽  
Data Analytics ◽  
Large Datasets ◽  
Securities And Exchange Commission ◽  
Financial Report ◽  
Business Reporting ◽  
Accounting Curriculum ◽  
Combining Data ◽  
Real World Datasets

This advisory case is designed to develop data analytics skills using multiple large real-world datasets based on eXtensible Business Reporting Language (XBRL). This case can also be used to introduce students to XBRL concepts such as extension taxonomies. Students are asked to recommend an XBRL preparation software for a hypothetical company (ViewDrive) that is adopting XBRL to satisfy the financial report filing requirements imposed by the Securities and Exchange Commission (SEC). Students perform data cleansing (extract, transform, load) procedures to prepare large datasets for data analytics. Students are encouraged to think critically, specify assumptions before performing data analytics (using analytic software such as Tableau), and generate visualizations that support their written recommendations. The case is easy to implement, promotes active learning, and has received favorable student and instructor feedback. This case can be used to introduce technology and data analytics topics into the accounting curriculum to help satisfy AACSB’s objectives.

Relevance of big data to forensic accounting practice and education

2019 ◽  
Vol 34 (3) ◽  
pp. 268-288 ◽  
Author(s):  
Zabihollah Rezaee ◽  
Jim Wang
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Accounting Education ◽  
Content Type ◽  
Accounting Practice ◽  
Accounting Curriculum ◽  
Forensic Accounting ◽  
Accounting Courses ◽  
Challenges And Opportunities ◽  
Practical Implications

Purpose This paper aims to examine the relevance of Big Data to forensic accounting practice and education by gathering opinions from a sample of academics and practitioners in China. Design/methodology/approach The authors conduct a survey of academics and practitioners regarding the desired demand, importance and content of Big Data educational skills and topics for forensic accounting education to effectively respond to challenges and opportunities in the age of Big Data. Findings Results indicate that the demand for and interest in Big Data/data analytics and forensic accounting will continue to increase; Big Data/data analytics and forensic accounting should be integrated into the business curriculum; many of the suggested Big Data topics should be integrated into forensic accounting education; and some attributes and techniques of Big Data are important in improving forensic accounting education and practice. Research limitations/implications Readers should interpret the results with caution because of the sample size (95 academics and 103 practitioners) and responses obtained from academics and practitioners in one country (China) that may not be representative of the global population. Practical implications The results are useful in integrating Big Data topics into the forensic accounting curriculum and in redesigning the forensic accounting courses/programs. Social implications The results have implications for forensic accountants in effectively fulfilling their responsibilities to their profession and society by combating fraud. Originality/value This study provides educational, research and practical implications as Big Data and forensic accounting are advancing.

Infusing data analytics into the accounting curriculum: A framework and insights from faculty

2018 ◽  
Vol 43 ◽  
pp. 24-39 ◽  
Author(s):  
Ann C. Dzuranin ◽  
Janet R. Jones ◽  
Renee M. Olvera
Keyword(s):  
Data Analytics ◽  
Accounting Curriculum
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