Özet:

Today, in the data environments where the phenomenon of digitalization is increasingly spread, big data needs are facing us from day to day in different form structures. Big data is complex, volume, and growing data. Big data Industry 4.0, data mining, innovative innovations and changes in cloud substructure systems have gained the ability to easily store in many databases with fast network features. Therefore, big data has gained a dynamic, physical, biological pace in many disciplines of science. Specifically, HDFS (Hadoop Distrubuted File System) and Hadoop components have retained their place among the most popular applications in large data sets. Today we see the big data relationship being more popular in software engineering, food engineering, hardware engineering, health research, coding training, industrial modeling. Depending on the fact that the geographical data is technologically self-reviewed, the geographical data in question has now entered the influence of large databases. Because it has become difficult to fully understand the digital world and digital geography processes without big data. The intrusion of the spatial tradition of geographical science with spatial analysis has directed geographical science to modern technological applications, geography and statistical-based processes, programs. In this sense, the main objectives of this study are: to highlight the use and prevalence of big data with the plant geography databases created, to briefly discuss the technological applications and algorithms used that are important in the accumulation of big data, to compare the similarities and differences between big data and geographical data, to try to compare the uses, to highlight the relative link between the big data Hadoop strategy and the basic components with the hardware language examples, etc. Working for purposes has been done. The scope of the study included big data, geographical data, big data components, big data accumulation techniques and algorithms, plant data bases, big data uses and data mining applications. The work was conducted in a theoretical framework. The relevant literary scan is followed by discipline in the form of planning, research and finding of resources, the study of resources, the preparation of literary documents and the transfer of literature to the text, writing. The research method is preferred as the qualitative research method. In terms of the research design and methods, the positive paradigm methodology was preferred in the research, since the fundamentally positivist approach was driven. From the point of view of the positivist methodology, the study has also been applied to the way of "total balance" in the way of obtaining information. In this context, the study in terms of quantitative types of research is also included in the type of "Statistical research". Since the study is part of the statistical type of research, it has been mainly included in statistical analysis, mathematical modelling in terms of data collection and analysis techniques. The study’s findings have previously created a sample of large geographical data sets within themselves, divided into systematic dimensions, and attempted to study with the MAP Reduce relative link. The data blocks created with the download calculation are combined with key values, pairs, key groups, reduction (reduce). The data was later enriched with the schematic exhibitions of Eşle-Download word counting. The example was then evaluated in itself by holding the big geographical data subject to comparison with large data samples. Global Biodiversity Informatıon Facılıty data sets have been used for the distribution database of specific species. In the result section of the study, the information obtained in the findings and the produced data Table, shape and schematic representations were evaluated, the study was attempted to reveal the innovations on the existing geographical literature and plant geography research. The study also studied big data phenomena, big data applications, big data analytics and sizes.