Büyük Veri: Sosyal Bilimler ile Eğitim Bilimlerinde Kullanımı ve Uygulama Alanları

Bu çalışmanın amacı özellikle son on yılda üzerinde en fazla konuşulan konulardan biri olan büyük verinin ne olduğu ve sosyal bilimlerde büyük verinin nasıl ele alındığının belirlenmesidir. Bu amaç kapsamında öncelikle büyük veriyi tanımlarken veri hacmi (volume), veri çeşitliliği (variety) ve veri akış hızı (velocity) kavramlarının baş harfleri alınarak yapılan 3V tanımı ve daha sonra verinin gerçekliği (veracity) ile verinin değeri (value) kavramlarının eklenmesiyle ortaya çıkan 5V ifadesinin ne olduğu açıklanmıştır. Bununla birlikte çalışmada büyük veri kaynakları, büyük veri türleri ve klasik anlamda ele alınan veri ile büyük veri arasındaki farklılıkların neler olduğu açıklanmıştır. Bunun yanında büyük veri analizinde kullanılan program ve yazılımların neler olduğu, farklı ortamlardaki büyük verilerin nasıl ele alınacağına ilişkin kavramsal olarak neler yapıldığı açıklanmaya çalışılmıştır. Çalışmada son olarak sosyal bilimlerde ve eğitim bilimlerinde büyük verinin nasıl tanımlandığı, hangi tür verilerin büyük veri olarak kabul edilebileceği, büyük verilerin analizinde güncel yazılımların ve programların neler olduğu açıklanmıştır. Çalışma özellikle sosyal bilimlerde ve eğitim bilimlerinde çalışma yapacak araştırmacılara büyük verinin ne olduğu, nasıl ele alınması gerektiği ve büyük veri uygulamalarında kullanılan yazılımlara ilişkin önemli bilgiler sunulmaktadır.

Big Data: Its Use and application area in Social Sciences and Educational Sciences

The aim of this study is to determine what big data is, one of the most talked about topics in the last decade, and how big data is handled in the social sciences. Within the scope of this aim, the definition of large data, the volume of data (volume), data variety and variety of data velocity concepts of the 3V definition and then the verbs of the data (veracity) with the addition of value (value) 5V is explained. However, in this study, big data sources, large data types and the data discussed in the classical sense, and the differences between big data are explained. In addition, the attempt is made to explain what are the programs and the software that is used in big data analysis, and what is done conceptually about how big data in different environments will be handled. Finally, it is explained how big data is defined in the social sciences and educational sciences, what kind of data can be accepted as big data, the current software and programs in analyzing big data. The study presents important information about what is big data, how it should be handled, and the software used in large data applications, especially for researchers who will work in the social sciences and educational sciences.

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