Data Analysis of Various Terrorism Activities Using Big Data Approaches on Global Terrorism Database

Data Analysis of Various Terrorism Activities Using Big Data Approaches on Global Terrorism Database

연구 분야: Databases

학회: 2020 Sixth International Conference on Parallel, Distributed and Grid Computing (PDGC)

The field of data science is getting wide day by day and more areas are using this concept. This paper uses the concept of data science for analyzing patterns of terrorism globally. We use the “Global Terrorism Database (GTD)” having information of terrorist attacks around the world from 1970 to 2017. The data was preprocessed and we use “Hive Query Language (HiveQL)” and Hadoop concepts to make various predictions out of the database. HiveQL is run by intergrating with Hadoop which is installed on a linux system. Various interesting findings were made from this database which are represented in the form of queries that were shot on the database. The queries were decided upon by framing a few questions and finding suitable answers. The results obtained are presented graphically using tableau and python for a better understanding of the reader. In the last section, various inferences were drawn from the results obtained.