MUHASEBE UYGULAMALARI ÜZERİNE İŞ ZEKASI ÇÖZÜMLERİNİN ETKİSİ: KAVRAMSAL BİR BAKIŞ

Year 2025, Volume: 5 Issue: 2, 188 - 205, 21.10.2025

Fatih Ömür Binici

https://doi.org/10.71284/jpepfm.202525

Abstract

İş Zekâsı (İZ), işletmelerde karar verme süreçlerini destekleyen ve rekabet avantajı sağlayan kritik bir teknoloji olarak tanımlanmaktadır. Aynı zamanda İZ, ham verileri anlamlı bilgilere dönüştüren yöntem, teknik, sistem ve uygulamalar bütününü ifade eder. Özellikle belirsiz ve rekabetçi piyasa koşullarında, kurumların hayatta kalması ve sürdürülebilir stratejik başarı elde edebilmesi için İZ sistemleri vazgeçilmez bir rol üstlenmektedir. İZ sistemleri, işletme içi ve dışı kaynaklardan elde edilen bilgileri analiz ederek karar vericilere zamanında ve doğru bilgi sunmakta; performans ölçümü, pazar eğilimlerinin öngörülmesi, operasyonel süreçlerin optimizasyonu gibi pek çok alanda değer katmaktadır. Muhasebe bilgi sistemi ile entegrasyonunda ise finansal verilerin izlenmesi, raporlama etkinliğinin artırılması, denetim işlevlerinin güçlendirilmesi ve gelir-gider kalıplarının analiz edilmesi gibi işlevler ile öne çıkmaktadır. Bu bağlamda çalışmanın amacı, muhasebe alanında iş zekâsı sistemlerinin kullanımını inceleyerek karar alma süreçlerine sağladığı katkıları, raporlama etkinliğini ve muhasebe fonksiyonlarındaki dönüşüm potansiyelini ortaya koymaktır. Ayrıca iş zekâsı teknolojilerinin muhasebe süreçlerinde benimsenme düzeyleri, sağladığı avantajlar ve karşılaşılan sınırlılıkların sistematik biçimde değerlendirilmesi hedeflenmektedir. Çalışmanın alan yazınına katkısı, muhasebe yöneticileri, denetçiler ve finansal analistlere, iş zekâsı çözümlerini stratejik rekabet avantajına dönüştürme konusunda yol gösterici bulgular sunması beklenmektedir.

Keywords

Finansal Muhasebe , İş Zekâsı , Muhasebe Bilgi Sistemi

THE IMPACT OF BUSINESS INTELLIGENCE SOLUTIONS ON ACCOUNTING APPLICATIONS: A CONCEPTUAL PERSPECTIVE

Abstract

Business Intelligence (BI) is defined as a critical technology that supports decision-making processes and provides competitive advantage in businesses. In the literature, BI refers to the set of methods, techniques, systems, and applications that transform raw data into meaningful information. Especially in uncertain and competitive market conditions, BI systems play an indispensable role in organizations' survival and sustainable strategic success. BI systems analyze information obtained from internal and external sources to provide decision-makers with timely and accurate information, adding value in many areas such as performance measurement, market trend prediction, and operational process optimization. Integration with accounting information systems highlights functions such as monitoring financial data, increasing reporting efficiency, strengthening auditing functions, and analyzing income-expense patterns. In this context, the aim of this study is to examine the use of BI systems in accounting and to reveal their contributions to decision-making processes, reporting effectiveness, and the potential for transformation in accounting functions. Furthermore, it aims to systematically evaluate the adoption levels, advantages, and limitations of BI technologies in accounting processes. The contribution of the study to the literature is that it provides guiding findings for accounting managers, auditors and financial analysts in transforming business intelligence solutions into strategic competitive advantage.

Keywords

Financial Accounting , Business Intelligence , Accounting Information System

References

• Abdelhalim, A. M. (2023). How management accounting practices integrate with big data analytics and its impact on corporate sustainability. Journal of Financial Reporting and Accounting. https://doi.org/10.1108/jfra-01-2023-0053
• Akter, S., Hossain, M. A., Tarba, Y., & Leonidou, E. (2023). How does quality-dominant logic ensure marketing analytics success and tackle business failure in industrial markets?. Industrial Marketing Management, 109, 44-57. https://doi.org/10.1016/j.indmarman.2022.12.005
• Al-Zubi, Z., Shaban, O. S., & Alnaser, N. (2014). The effect of business intelligence tools on raising the efficiency of modern management accounting. International Review of Management and Business Research, 3(1), 68.
• Araújo, L., Behr, A., & Schiavi, G. S. (2023). Adoption of business analytics in accounting. Revista Contabilidade & Finanças, 34(93), e1771 https://doi.org/10.1590/1808-057x20231771.en
• Bălăceanu, D. (2007). Components of a Business Intelligence software solution. Informatica Economică, 2(42), 67-73. https://EconPapers.repec.org/RePEc:aes:infoec:v:xi:y:2007:i:2:p:67-73
• Bany Mohammad, A., Al-Okaily, M., Al-Majali, M., & Masa’deh, R. (2022). Business Intelligence and Analytics (BIA) Usage in the Banking Industry Sector: An Application of the TOE Framework. Journal of Open Innovation: Technology, Market, and Complexity, 8(4), 189. https://doi.org/10.3390/joitmc8040189
• Bharadiya, J. P. (2023). A comparative study of business intelligence and artificial intelligence with big data analytics. American Journal of Artificial Intelligence, 7(1), 24.
• Carver, A., & Ritacco, M. (2006). The Business Value of Business Intelligence. A Framework for Measuring the Benefits of Business Intelligence. Business Objects, 33. https://dl.acm.org/doi/abs/10.5555/773287
• Chaudhuri, S., Dayal, U., & Narasayya, V. (2011). An overview of business intelligence technology. Communications of the ACM, 54(8), 88-98. https://doi.org/10.1145/1978542.1978562
• Chee, T., Chan, L. K., Chuah, M. H., Tan, C. S., Wong, S. F., & Yeoh, W. (2009, December). Business intelligence systems: state-of-the-art review and contemporary applications. In Symposium on progress in information & communication technology (Vol. 2, No. 4, pp. 16-30).
• Chen, H., Chiang, R. H. L., & Storey, V. C. (2010). Business intelligence and analytics: From big data to big impact. MIS Quarterly, 36(4), pp. 1165-1188. https://doi.org/10.2307/41703503
• Chu, M. K., & Yong, K. O. (2021). Big Data Analytics for Business Intelligence in Accounting and Audit. Open Journal of Social Sciences, 9, 42- 52. https://doi.org/10.4236/jss.2021.99004
• Correia, J., Santos, M. Y., Costa, C., & Andrade, C. (2018, September). Fast online analytical processing for big data warehousing. In 2018 International Conference on Intelligent Systems (IS) (pp. 435-442). IEEE. https://doi.org/10.1109/IS.2018.8710583
• Dubey, R., Gunasekaran, A., Childe, SJ, Blome, C. ve Papadopoulos, T. (2019). Büyük veri ve öngörücü analiz ve üretim performansı: kurumsal teori, kaynak temelli bakış açısı ve büyük veri kültürünün entegrasyonu. British Journal of Management, 30 (2), 341-361. https://doi.org/10.1111/1467-8551.12355
• Elbashir, M. Z., Collier, P. A., & Davern, M. J. (2008). Measuring the effects of business intelligence systems: The relationship between business process and organizational performance. International journal of accounting information systems, 9(3), 135-153.https://doi.org/10.1016/j.accinf.2008.03.001
• Elena, C. (2011). Business intelligence. Journal of Knowledge Management, Economics and Information Technology, 1(2), 1-12. https://ideas.repec.org/a/spp/jkmeit/1102.html
• Elgendy, N., Elragal, A., & Päivärinta, T. (2022). DECAS: a modern data-driven decision theory for big data and analytics. Journal of Decision Systems, 31(4), 337-373. https://doi.org/10.1080/12460125.2021.1894674
• Fan, W., & Gordon, M. D. (2014). The power of social media analytics. Communications of the ACM, 57(6), 64-73. https://doi.org/10.1145/2602574
• Freudenreich, T., Furtado, P., Koncilia, C., Thiele, M., Waas, F., & Wrembel, R. (2012, August). An on-demand ELT architecture for real-time BI. In International Workshop on Business Intelligence for the Real-Time Enterprise (pp. 50-59). Berlin, Heidelberg: Springer Berlin Heidelberg.
• Gangadharan, G. R., & Swami, S. N. (2004). Business intelligence systems: Design and implementation strategies. In Proceedings of the 26th International Conference on Information Technology Interfaces (pp. 135-140).
• Gaol, Ford Lumban, Abdillah, Lufty and Matsuo, Tokuro. "Adoption of Business Intelligence to Support Cost Accounting Based Financial Systems — Case Study of XYZ Company" Open Engineering, vol. 11, no. 1, 2021, pp. 14-28. https://doi.org/10.1515/eng-2021-0002
• Geddes, Bruce H. (2020). Emerging Technologies in Management Accounting. In: Journal of Economics and Business, Vol.3, No.1, 152-159. https://doi.org/10.31014/aior.1992.03.01.185
• Gibson, M. C., Arnott, D. R., & Jagielska, I. (2004). Evaluating the intangible benefits of Business Intelligence: review & research agenda. In R. Meredith, G. Shanks, D. Arnott, & S. Carlsson (Eds.), Decision Support in an Uncertain World: Proceedings of the 2004 IFIP International Conference on Decision Support Systems (DSS2004) (pp. 295- 305). Monash University. https://research.monash.edu/en/publications/evaluating-the-intangible-benefits-of-business-intelligence-revie
• Haije, E. G. (2025, July 29). Top 15 business intelligence tools in 2025: An overview. Mopinion. access date: 21/08/2025 https://mopinion.com/business-intelligence-bi-tools-overview/
• Hedgebeth, D. (2007), "Data‐driven decision making for the enterprise: an overview of business intelligence applications", VINE, Vol. 37 No. 4, pp. 414-420. https://doi.org/10.1108/03055720710838498
• Jones, V. A. (2024). Business Intelligence Solutions for Enhanced Accounting Decision-Making in Digital Transformation. Engineering Science Letter, 3(01), 11–15. https://doi.org/10.56741/esl.v3i01.468
• Köklü, K. (2018). İş analizi, iş analistliği ve iş zekâsı. lectio socialis, 2(2), 121-142. https://dergipark.org.tr/en/pub/lectio/issue/38656/398318
• Luhn, H. P. (1958). A business intelligence system. IBM Journal of research and development, 2(4), 314-319. https://doi.org/10.1147/rd.24.0314
• Miškuf, M., & Zolotová, I. (2015, January). Application of business intelligence solutions on manufacturing data. In 2015 IEEE 13th International Symposium on Applied Machine Intelligence and Informatics (SAMI) (pp. 193-197). IEEE. https://doi.org/10.1109/SAMI.2015.7061874
• Morshed A, Ramadan A, & Maali B (2024). Transforming accounting practices: The impact and challenges of business intelligence integration in invoice processing. Journal of Infrastructure, Policy and Development. 8(6): 4241. https://doi.org/10.24294/jipd.v8i6.4241
• Munteanu, A., & Puican, F. (2012). Mobile analytics: Modern decision support systems. Revista Economica-Applied Informatics in Economy, 5, 139-146. https://EconPapers.repec.org/RePEc:blg:reveco:v:supplement:y:2012:i:5:p:139-146
• Nah, F. F.-H., Lau, J. L.-S., & Kuang, J. (2001). Critical success factors for ERP implementations. Journal of Computer Information Systems, 41(3), 23–29. https://doi.org/10.1080/08874417.2001.11647010
• Nespeca, A., & Chiucchi, M. S. (2018). The impact of business intelligence systems on management accounting systems: the consultant’s perspective. In Network, Smart and Open: Three Keywords for Information Systems Innovation (pp. 283-297). Cham: Springer International Publishing
• Olszak, C. M., & Ziemba, E. (2003, June). Business intelligence as a key to management of an enterprise. In Proceedings of informing science and IT education conference (Vol. 10, pp. 855-863). https://doi.org/10.28945/2672
• Pałys, M., & Pałys, A. (2023). Benefits and challenges of self-service business intelligence implementation. Procedia Computer Science, 225, 795-803. https://doi.org/10.1016/j.procs.2023.10.066
• Patel, J. A., & Sharma, P. (2020). Online analytical processing for business intelligence in big data. Big data, 8(6), 501-518. https://doi.org/10.1089/big.2020.0045
• Pazarçeviren, S. Y., Zor, Ü., & Gürbüz, F. (2015). İş Zekâsı: Kavramsal Çerçeve, Bileşenler ve İşleyiş. Siyaset, Ekonomi ve Yönetim Araştırmaları Dergisi, 3(1), 75-91. https://dergipark.org.tr/en/pub/seyad/issue/53397/710132
• Peng, Y., Ahmad, F., & Ahmad, A. Y. A. B. (2023). Riding the Waves of Artificial Intelligence in Advancing Accounting and Its Implications for Sustainable Development Goals. Sustainability, 15(19), 14165.
• Popovič, A., Hackney, R., Coelho, P. S., & Jaklič, J. (2012). Towards business intelligence systems success: Effects of maturity and culture on analytical decision making. Decision support systems, 54(1), 729-739. https://doi.org/10.1016/j.dss.2012.08.017
• Rahman, A. A., Hasan, N. A., & Lahad, N. A. (2016). Issues and challenges in business intelligence case studies. Jurnal Teknologi (Sciences & Engineering), 78(8-2). https://doi.org/10.11113/jt.v78.9554
• Ranjan, J. (2009). Business intelligence: Concepts, components, techniques and benefits. Journal of theoretical and applied information technology, 9(1), 60-70. https://www.jatit.org/
• Renaldo, N., Suhardjo, Suharti, Suyono, & Cecilia. (2022). Optimizing Company Finances Using Business Intelligence in Accounting. Journal of Applied Business and Technology, 3(2), 209-213. https://doi.org/10.35145/jabt.v3i2.107 Rice, M. (2024). 21 business intelligence applications and examples to know. Built In. Access date: 21/08/2025 (https://builtin.com/articles/business-intelligence-examples-applications
• Saqib, M., Al Toobi, S., Al Nadhiri, F., & Younus, F. (2018, March). Integrating knowledge management and business intelligence practices to improve organizational performance. In 2018 Majan International Conference (MIC) (pp. 1-10). IEEE. https://doi.org/10.1109/MINTC.2018.8363154
• Seker, S. E. (2016). İş Zekâsı (Business Intelligence). YBS Ansiklopedi, 3(1), 21-25. https://ybsansiklopedi.com/cilt-3-sayi-1-mart-2016/
• Tamandeh, S. H. (2016). The effect of business intelligence on management accounting information system. European Online Journal of Natural and Social Sciences, 5(1), 190-199. http://www.european-science.com/
• Tavera Romero, C. A., Ortiz, J. H., Khalaf, O. I., & Ríos Prado, A. (2021). Business intelligence: business evolution after industry 4.0. Sustainability, 13(18), 10026. https://doi.org/10.3390/su131810026
• Thompson, W. J., & Van der Walt, J. S. (2010). Business intelligence in the cloud. South African Journal of Information Management, 12(1), 1-15. https://hdl.handle.net/10520/EJC46328
• Turban, E., Sharda, R., & Delen, D. (2011). Decision support and business intelligence systems (9th ed.). Pearson Education, India.
• Tutunea, M. F. (2015). Mobile business intelligence solutions. Procedia Economics and Finance, 32, 162–169. https://doi.org/10.1016/S2212-5671(15)01379-4
• Tvrdíková, M. (2007, June). Support of decision making by business intelligence tools. In 6th International Conference on Computer Information Systems and Industrial Management Applications (CISIM'07) (pp. 364-368). IEEE. https://doi.org/10.1109/CISIM.2007.64
• Yassin, M. M., & Toumeh, A. A. (2024). Innovative approaches to accounting education: incorporating business intelligence tools. Cogent Business & Management, 11(1), 2414851.https://doi.org/10.1080/23311975.2024.2414851
• Zamil, M. H., Mohiuddin, M., & Mamun, M. N. H. (2024). Business intelligence systems in finance and accounting: A review of real-time dashboarding using Power BI & Tableau. American Journal of Scholarly Research and Innovation, 3(2), 52–79.https://doi.org/10.63125/fy4w7w04
• Zeng, L., Xu, L., Shi, Z., Wang, M., & Wu, W. (2006, October). Techniques, process, and enterprise solutions of business intelligence. In 2006 IEEE international conference on systems, man and cybernetics (Vol. 6, pp. 4722-4726). IEEE. https://doi.org/10.1109/ICSMC.2006.385050