BÜYÜK VERİ’NİN V’leri ve VERİ ANALİTİĞİ

Year 2022, Issue: 51, 361 - 378, 09.08.2022

Ayşe Yıldız

https://doi.org/10.30794/pausbed.1117208

Cited By: 1

Abstract

Bilgisayar teknolojisindeki gelişmelerle birlikte büyük veri günümüzün en dikkat çekici konularından biri olmaya devam etmektedir. 2000’li yıllarında Büyüklük (Volume), Hız (Velocity) ve Çeşitlilik (Variety) özellikleri ile tanımlanmaya çalışılan bu kavram 20 yıllık bir dönem içinde her geçen zamanda kendisine yeni bir V ekleyerek 50’ye V’li özelliğe sahip olarak karşımıza çıkmış durumdadır. Belli ki bu bu V’lerde artış devam edecektir. Çalışmada literatürde en çok karşılaşılan 30’un üzerindeki V’li kavramlar tanıtılmış ve diğer kavramlar için kaynak önerilerinde bulunulmuştur. Ancak büyük veriyi bu kadar önemli kılan hiç şüphesiz onun bu ham hali değil, veri analitiği denilen tekniklerle işlenerek bilgiye dönüştürülmesi ve karar verme sürecinde kullanılan en önemli girdilerinden birini oluşturmasıdır. Bu çalışmada veri analitiği kavramına ilişkin bilgiler sunulmuş, veri kaynakları ile kullanılma amaçları bakımından veri analitiği bir sınıflandırmaya tabi tutulmuştur. Son olarak da işletmeler başta olmak üzere kuruluşların bu büyük veriden ve veri analitiğinden sağlayabilecekleri faydalar sıralanmıştır. Çalışma bu kadar büyük bir konunun belirli boyutlarını ele almıştır, ancak bu konu gelişime açıktır. İleriki çalışmalarda veri analitiğinde kullanılan araçlar ve tekniklere, veri analitiğinde karşılaşılan sorunlara ve ileride gözlemlenebilecek trendlere ilişkin bilgiler sunularak çalışma geliştirilebilir.

Keywords

Büyük veri, Veri analitiği, Veri analitiği türleri

V’s of BIG DATA and DATA ANALYTICS

Abstract

With the developments in computer technology, big data continues to be one of the most remarkable issues today. This concept, which was tried to be defined with the features of Volume, Velocity and Variety in the 2000s, has emerged as a 50-V feature by adding a new V to itself over a 20-year period. Obviously these Vs will continue to increase. In the study, more than 30 most common V concepts in the literature were introduced and resource suggestions were made for other concepts. However, what makes big data so important is undoubtedly not its raw form, but the fact that it is transformed into information by processing with techniques called data analytics and constitutes one of the most important inputs used in the decision-making process. In this study, information on the concept of data analytics has been presented, and data analytics has been classified in terms of data sources and purposes of use. Finally, the benefits that organizations, especially businesses, can derive from this big data and data analytics are listed. The study has addressed certain aspects of such a large topic, but it is open to improvement. The study can be improved by presenting information about the tools and techniques used in data analytics, the problems encountered in data analytics, and the trends that can be observed in the future in future studies.

Keywords

Big Data, Data analytics, Types of data analytics

References

• Akay, E. Ç. (2018). “Ekonometride yeni bir ufuk: Büyük veri ve makine öğrenmesi”. Sosyal Bilimler Araştırma Dergisi, 7(2), 41-53.
• Aktan, E. (2018). “Büyük veri: Uygulama alanları, analitiği ve güvenlik boyutu”. Bilgi Yönetimi, 1(1), 1-22.
• Altunışık, R. (2015). “Büyük Veri: Fırsatlar Kaynağı mı Yoksa Yeni Sorunlar Yumağı mı?" Yildiz Social Science Review, 1(1), 45-76.
• Amalina, F., Hashem, I. A. T., Azizul, Z. H., Fong, A. T., Firdaus, A., Imran, M., ve Anuar, N. B. (2019). “Blending big data analytics: Review on challenges and a recent study”. IEEE Access, 8, 3629-3645.
• Arena, F., ve Pau, G. (2020). “An overview of big data analysis”. Bulletin of Electrical Engineering and Informatics, 9(4), 1646-1653.
• Artun, O., ve Levin, D. (2015). Predictive marketing: easy ways every marketer can use customer analytics and big data. John Wiley ve Sons.
• Banerjee, A., Bandyopadhyay, T., ve Acharya, P. (2013). “Data analytics: Hyped up aspirations or true potential?”. Vikalpa, 38(4), 1-12.
• Big Data Analytics (Mayıs, 2018). “What it is and why it matters, SAS”, (Erişim Tarihi: 11 May 2022, https://www.sas.com/en_us/insights/analytics/bigdata-analytics.html
• Bilik, M., ve Aydın, Ü. (2018). Finansal Hizmetlerde Dijital Dönüşüm ve Etkileri. In Book of Proceedings 3rd International Congress on Economics, Finance and Energy. ISBN: 978-601-7805-32-6:22.
• Chaudhari, P., ve Patel, B. (2017). “Future of big data. International research journal of engineering and technology, 4(1), 595-597. Chen, H., Chiang, R. H., ve Storey, V. C. (2012). Business intelligence and analytics: From big data to big impact”. MIS quarterly, 1165-1188.
• Cox, M., ve Ellsworth, D. (1997). “Application-controlled demand paging for out-of-core visualization”. In Proceedings. Visualization'97, IEEE, 235-244.
• Davenport, T. H. (2014). How strategists use “big data” to support internal business decisions, discovery and production. Strategy ve Leadership.
• Davenport, T. H., ve Dyché, J. (2013). “Big data in big companies”. International Institute for Analytics, 3(1-31).
• Dinh, L. T. N., Karmakar, G., ve Kamruzzaman, J. (2020). “A survey on context awareness in big data analytics for business applications”. Knowledge and Information Systems, 62(9), 3387-3415.
• Duan, L., ve Xiong, Y. (2015). “Big data analytics and business analytics”. Journal of Management Analytics, 2(1), 1-21.
• Gandomi, A., ve Haider, M. (2015). “Beyond the hype: Big data concepts, methods, and analytics”. International journal of information management, 35(2), 137-144.
• Grover, V., Chiang, R. H., Liang, T. P., ve Zhang, D. (2018).” Creating strategic business value from big data analytics: A research framework”. Journal of Management Information Systems, 35(2), 388-423.
• Hussien, A. A. (2020). How many old and new big data v’s characteristics, processing technology, and applications (bd1). International Journal of Application or Innovation in Engineering ve Management, 9(9), 15-27.
• Jeble, S., ve Patil, Y. (2016). “Role of big data and predictive analytics”. International Journal of Automation and Logistics, 2(4), 307-331.
• Jeble, S., Kumari, S., ve Patil, Y. (2018). Role of big data in decision making. Operations and Supply Chain Management: An International Journal, 11(1), 36-44.
• K. Borne, "Top 10 Big Data Challenges – A Serious Look at 10 Big Data V’s," 11 Mayıs 2022 tarihinde alındı. https://www.mapr.com/blog/top-10-big-datachallenges-%E2%80%93-serious-look-10-big-data-v%E2%80%99s. Kaisler, S., Armour, F., Espinosa, J. A., ve Money, W. (2013). “Big data: Issues and challenges moving forward. In 2013 46th Hawaii international conference on system sciences (pp. 995-1004). IEEE.
• Kapil, G., Agrawal, A., ve Khan, R. A. (2016). “A study of big data characteristics”. In 2016 International Conference on Communication and Electronics Systems (ICCES) (pp. 1-4). IEEE.
• Laney, D. (2001). “3D Data management: Controlling data volume, velocity and variety”. META group research note, 6(70), 1. Malik, R. S.2022, Big data in Social Media: How Big Data Can Be Used to Better Analyze Social Media Participation https://medium.datadriveninvestor.com/big-data-in-social-media-how-big-data-can-be-used-to-better-analyze-social-media-participation-9ff2702de43d
• Naganathan, V. (2018). “Comparative analysis of Big data, Big data analytics: Challenges and trends”. International Research Journal of Engineering and Technology (IRJET), 5(05), 1948-1964.
• Oguntimilehin A., ve Ademola E.O. (2014). ‘‘A Review of Big Data Management, Benefits and Challenges,’’ Journal of Emerging Trends in Computing and Information Sciences, Vol-5, 33-437.
• Panimalar, A., Shree, V., ve Kathrine, V. (2017). “The 17 V’s of big data”. International Research Journal of Engineering and Technology (IRJET), 4(9), 3-6.
• Rajaraman, V. (2016). “Big data analytic”s. Resonance, 21(8), 695-716.
• Shafer, T. (April, 2017). The 42 V’s of Big Data and Data Science. 9 Mayıs 2020 tarihinde alındı. https://www.kdnuggets.com/2017/04/42-vs-big-data-data-science.html
• Souza, G. C. (2014). “Supply chain analytics”. Business Horizons, 57(5), 595-605.
• Storey, V. C., ve Song, I. Y. (2017). “Big data technologies and management: What conceptual modeling can do”. Data ve Knowledge Engineering, 108, 50-67.
• Sun, Z., Strang, K., ve Firmin, S. (2017). “Business analytics-based enterprise information systems”. Journal of Computer Information Systems, 57(2), 169-178.
• Vassakis, K., Petrakis, E., ve Kopanakis, I. (2018). “Big data analytics: applications, prospects and challenges”. In Mobile big data (pp. 3-20). Springer, Cham.
• Waller, M. A., ve Fawcett, S. E. (2013). “Data science, predictive analytics, and big data: a revolution that will transform supply chain design and management”. Journal of Business Logistics, 34(2), 77-84.
• Wang, R. (2012). 10 Mayıs 2022 tarihinde alındı. https://enterpriseirregulars.com/46120/beyond-the-three-vs-of-big-data-viscosity-and-virality/