Title: Accounting analytics data types and structures: an educational perspective

Authors: Saeed Askary; Davood Askarany; Yusuf Joseph Ugras

Addresses: Australian Business and Management Consultancy (ABMC), Melbourne, Burwood East, VIC, 3151, Australia ' Department of Accounting and Finance, School of Business, The University of Auckland, Private Bag: 92019, New Zealand ' Accounting Department, School of Business, La Salle University, 1900 West Olney Ave., Philadelphia, PA 19141, USA

Abstract: Technological changes have affected the accounting profession significantly, so the next generation of accountants in the future digital economy must develop strong analytical skills. Despite this need, no research has connected data type and structure to accounting values. This paper discusses data types and structures for big data projects in accounting analytics and what teaching techniques are suitable for accounting students. The paper further demonstrates the relationship between data type in the data lifecycle and warehouse and explains data quality issues. We provide a detailed view of the relationship between data type and structure and suggest that flipped learning can efficiently teach data structure to accounting students. We further discuss how analytical techniques can be applied more effectively by using the flipped learning method.

Keywords: accounting analytics; accounting data type; data lifecycle; data structure; data warehouse; accounting education.

DOI: 10.1504/IJMDM.2024.140724

International Journal of Management and Decision Making, 2024 Vol.23 No.5, pp.562 - 585

Received: 08 Nov 2022
Accepted: 05 Jan 2023
Published online: 02 Sep 2024 *

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