Big Data in Health and the Importance of Data Visualization Tools Sa˘ glıkta Büyük Veri ve Veri Görselle¸ stirme Araçların Önemi Fehmi Skender 1,∗ , Ilker Ali 1 1 Department of Computer Engineering, International Vision University, Gostivar, North Macedonia ORCIDs: 0000-0001-6046-5772, 0000-0002-2111-415X E-mails: fehmi.skender@vizyon.edu.mk, ilker@vizyon.edu.mk ∗ Corresponding author. Abstract—Big data concepts are increasing with their spatial speed, from personal information to extensive volume data. Since the human brain perceives visual data faster, the data must be processed and displayed appropriately. As in all areas of life, the size of the data obtained in the health sector has increased rapidly. Data storage and security have gained importance with the excessive increase in data. Big data, data mining, and visualization tools have become increasingly important to process and use data for valuation purposes. Therefore, the visualization of data and the use of analysis tools play a significant role in data processing and decision-making in the development of the health sector. The importance of data visualization tools in the health sector will become increasingly indispensable. There are many software tools developed for these purposes. This study’s literature review explained the basic concepts of big data and data visualization. Research in the health sector around the world was summarized. In addition to this literature review, analyses with comparison and deduction research methods were also carried out. As a result, suggestions were made by making predictions for future studies in the health sector. Keywords—big data; data visualization; health sector Özetçe—Büyük veri kavramları ki¸ sisel bilgilerinden ba¸ slayarak büyük hacimli verilerine kadar uzaysal hızı ile artı¸ s göster- mektedir. ˙ Insan beyni görsel verileri daha hızlı bir ¸ sekilde algıladı˘ gından dolayı verilerin de uygun olarak i¸ slenme ve gösterilmesi gerekmektedir. Ya¸ samın her alanında oldu˘ gu gibi sa˘ glık sektöründe de elde edilen verilerin boyutu hızlı bir ¸ sekilde artmı¸ stır. Verilerin a¸ sırı artı¸ sı ile birlikte, verilerin saklanması ve güvenli˘ ginin sa˘ glanması da önem kazanmı¸ stır. Verilerin i¸ slenmesi ve faydalı amaçlar için kullanabilmesi amacıyla büyük veri, veri madencili˘ gi ve veri görselle¸ stirme araçları giderek önem kazanmı¸ stır. Dolayısıyla, sa˘ glık sektörün geli¸ siminde verilerin i¸ slenmesi ve karar verilmesi konularında, verilerin görselle¸ stir- ilmesi ve analiz araçların kullanılması büyük rol ta¸ sımaktadır. Sa˘ glık sektöründe veri görselle¸ stirme araçların önemi gittikçe vazgeçilmez olaca˘ gı a¸ sikardır. Bu amaçlarla geli¸ stirilmi¸ s birçok yazılım aracı bulunmaktadır. Bu çalı¸ smada, büyük veri ve veri görselle¸ stirme temel kavramlarının açıklanması için literatür taraması yapılarak dünya genelinde sa˘ glık sektöründe yapılan ara¸ stırmalar özetlenmi¸ stir. Bu literatür taramasının yanı sıra, kar¸ sıla¸ stırma ve dedüksiyon ara¸ stırma yöntemleri ile analizler de gerçekle¸ stirilmi¸ stir. Sonuç olarak, sa˘ glık sektöründeki ilerde yapılması gereken çalı¸ smalar için tahminlerde bulunularak öner- iler yapılmı¸ stır. Anahtar Kelimeler—büyük veri; veri görselle¸ stirme; sa˘ glık sek- törü I. I NTRODUCTION Big data or “Big data” is an essential concept and has become a term very close to experts and ordinary citizens every day. Big data has recently become not just a popular term but a necessary and demanding term. It is mentioned that there is no end to the continuous interaction of software developers on the one hand and the user and business sector on the other. Along with big data, data processing and visualization is now an issue that interests everyone [1]. As in all areas of life, everyone is witnessing an increase in the volume of data, both personal and social. In the age of computers and smartphones, not only personal data but also the data of companies and organizations are increasing rapidly [2]. Data, the new trend of the 21st century, has made it difficult to extract meaningful information from it due to its increasing volume and diversity. Data analytics perspectives are broadly related to Big Data, wireless sensors, blogs, social media, emails, etc. collected from non-traditional sources such as In addition, companies can better understand large datasets by using big data analysis mechanisms. In this study, general information about the definition of big data, its relationship with other technologies, technologies used in the field of big data, and analysis techniques are given [3]. Big Data analytics can reveal bits of information hidden in too much data processing [4]. Big data has volume, variety, speed, variability, and reliability characteristics. Big Data evaluation consists of two classes: systematic use and reinforcement of new elements. Big data can be characterized by 6V data: value, volume, velocity, variety, veracity, and variability (Fig. 1) [5]. Journal of Intelligent Systems with Applications 2022; 5(1): 33-37 33