Analysis and Comparison of Business Intelligence Tools Most Preferred by Companies in Turkey

Year 2023, Volume: 11 Issue: 2, 144 - 155, 04.06.2023

Murat Ozdemir Eyüp Emre Ülkü Kazım Yıldız

https://doi.org/10.17694/bajece.1123171

Abstract

With the development of technology and the increase of the data sources, the size and variety of data collected from these sources has increased considerably. Thus, individuals and institutions have become able to store more data. However, it has become an important need to make meaning from this large and valuable data and transform into information and has become more complex. Business intelligence applications ensure that different types of data collected from different data sources are clustered and separated in a certain order and it provides the creation of reports by establishing a semantic relationship between these stored data. The aim of this study is identifying the business intelligence tools preferred by companies in Turkey. It is also aimed to give ideas to institutions and individual users so that they can choose the right business intelligence tool. Within the scope of the study, first of all, the general definition of business intelligence and the business intelligence applications preferred by the companies in Turkey in recent years are mentioned. Afterwards, the information obtained from the scanned scientific studies are analyzed and the findings are presented and then Afterwards, these tools were compared with the tables and it was aimed to give an idea to individuals and institutions. Scientific studies are very important in terms of revealing the current status of these business intelligence tools and seeing what kind of studies they can be used in the future.

Keywords

Business Intelligence, Qlik, Power BI, SAP BO, Tableau.

Supporting Institution

This study has been supported by Marmara University Scientific Research Projects Coordination Unit under grant number FYL-2022-10762.

Project Number

FYL-2022-10762.

References

• [1] H. Ates “Karar Vermede İş Zekasının Önemi: Tekstil Sektöründe Bir Araştırma”,T.C. Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü İşletme Anabilim Dalı Üretim Yönetimi ve Endüstri İşletmeciliği Programı Yüksek Lisans Tezi, 2008
• [2] S.Y. Pazarçeviren, Ü. Zor, F. Gürbüz. “İş Zekâsı: Kavramsal Çerçeve, Bileşenler ve İşleyiş” , Siyaset, Ekonomi ve Yönetim Araştırmaları Dergisi , Yıl:3, Cilt:3, 2015, Sayı:1
• [3] M. Sucu. "Karar Destek Sistemleri ve İş Zekâsı Uygulamalarının İşletmeler Açısından Önemi: Bir Literatür Araştırması" Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, Sayı 44, Denizli, ss., 2017, 261-283.
• [4] E. Ayçin., H. Aşan. “İş zekası uygulamaları seçimindeki kriterlerin önem ağırlıklarının FUCOM yöntemi ile belirlenmesi”. KOCATEPEİİBFD, 23(2), 2021, 195-208
• [5] M. Damar, G. Özdağoğlu, A. Özdağoğlu. “İş Zekasını ve İlgili Teknolojileri Konu Alan Araştırmalara Küresel Ölçekte Bilimetrik Bakış” , BEYDER / 2018, 13:2 (197-218).
• [6] K. Gowthami, M.R. Pavan Kumar. ”Study on Business Intelligence Tools for Enterprise Dashboard Development”, International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056 Volume: 04 Issue: 04 , Apr -2017.
• [7] D. Yıldız. “Bir İş Zekası Uygulaması ve Başarısının Değerlendirilmesi”, ASBİ Abant Sosyal Bilimler Dergisi, 2021, Cilt: 21, Sayı: 1/Bahar: 91-111.
• [8] https://www.kariyer.net/ (January 8, 2022).
• [9] https://www.kariyer.net/is-ilanlari/?kw=is%20zekasi&is=1 (January 8, 2022).
• [10] R.H.M.S. Ferreira, L.O. Figueiredo, R.B.C. Lima. “IIoT Solution for predictive monitoring based on vibration data from motors using Microsoft Azure machine learning studio and Power BI”, 2021 14th IEEE International Conference on Industry Applications.
• [11] https://docs.microsoft.com/en-us/power-bi/fundamentals/power-bi-overview (28.04.2022)
• [12] P. Rajesh, Bharadwaj, M. Alam, M. Tahernezhadi. “A Data Science Approach to Football Team Player Selection” ,2020 IEEE International Conference on Electro Information Technology (EIT)
• [13] J. Hewko, R. Sullivan, S. Reige, M. El-Hajj. “Data Mining in the NBA: An Applied Approach”, 2019 IEEE 10th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)
• [14] Z. Desai, K. Anklesaria, H. Balasubramaniam. “Business Intelligence Visualization Using Deep Learning Based Sentiment Analysis on Amazon Review Data”, 12th International Conference on Computing Communication and Networking Technologies (ICCCNT) | 978-1-7281-8595-8/21/2021.
• [15] https://www.sap.com/products/bi-platform.html (May 7, 2022).
• [16] https://www.techtarget.com/searchsap/definition/SAP-BusinessObjects-BI (May 7, 2022).
• [17] https://detaysoft.com/en-US/sap-analytics-cloud-pg-34 (May 7, 2022)
• [18] M. Kiula, C. Chege, K. Kahenya. “Application of Data Visualization for Improved Healthcare Insurance Management using QlikView”, IST-Africa 2019 Conference Proceedings Paul Cunningham and Miriam Cunningham (Eds) IIMC International Information Management Corporation, 2019 ISBN: 978-1-905824-62-2.
• [19] M.Kiula, C. Chege. “Identification of the Limitations of Healthcare Service/Insurance Industry ERPs on Data Flow using QlikView and MS Excel”, IST-Africa 2020 Conference Proceedings Miriam Cunningham and Paul Cunningham (Eds) IST-Africa Institute and IIMC, 2020 ISBN: 978-1-905824-65-6
• [20] R. Ilieva, K. Anguelov, D. Gashurova. “Monitoring and Optimization of e-Services in IT Service Desk Systems”, 2016 19th International Symposium on Electrical Apparatus and Technologies (SIELA)
• [21] A. Delgado, F. Rosas, C. Carbajal. “System of business intelligence in a health organization using the kimball methodology”, CHILECON 2019, October 29-31, Valpara´ıso, Chile
• [22] H. Musunuru, R. Lee, T. Matsuo. “Improving Lives Through Donation Analysis”, 2017 International Conference on Computational Science and Computational Intelligence
• [23] K. Mahatma, B. Waseso, W. Darwin. “The Design and Implementation of Data Visualization for Integrated Referral and Service System”, 2018 International Conference on ICT for Rural Development (IC-ICTRuDev)
• [24] B. Erazo, P. Peláez, J. Achig, , F.T. León, D. Marcillo. “Analysis of air pollution in single-family homes by using the time series”, 2017 12th Iberian Conference on Information Systems and Technologies (CISTI)
• [25] C.S. Reddy, R.S. Sangam , B.S. Rao. “A Survey on Business Intelligence Tools for Marketing, Financial, and Transportation Services”, Second International Conference on SCI 2018, Volume 2
• [26] D.M. Nazarov, A.D. Nazarov, D.B. KovtunBuilding. “Technology and Predictive Analytics Models in the SAP Analytic Cloud Digital Service” , 2020 IEEE 22nd Conference on Business Informatics (CBI)
• [27] S. Nararya, M. Saputra, W. Puspitasari. “Automation in Financial Reporting by using Predictive Analytics in SAP Analytics Cloud for Gold Mining Industry: a Case Study” , 2021 International Conference on ICT for Smart Society (ICISS)
• [28] D. M. Nazarov, D. B. Kovtun, T. N. Reichert. “SAP Analytics Cloud: intellectual analysis of small and medium-sized business activities in Russia in the context of COVID-19” , 2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)
• [29] https://www.youtube.com/watch?v=0QAXlWFTon4