A Survey on Visualization Techniques Used for Big Data Analytics

According to the recent developments and efficient technology trends, Big Data has become a vital asset for all industries and organizations in modern times. Big Data is trending due to few of the main reasons such as cloud migration initiated by companies, aggregation of digital unstructured and machine data, strong administration of data security permission, and many others. As we all know, analytics is the process of drawing conclusions and finding insights from a big pile. Big Data analytics is defined as the process of querying, simplifying, obtaining insights from the huge set of data integrated in the file systems of Big Data framework. The insights obtained as the outcome of analytics should reach the end users operating on the application platform in the form of visual representation techniques such as reports, line graphs, and bar charts for better understanding and exploration about the data. We propose a case study consisting of comparison of all the existing data visualization tools and techniques available and suitable with Big Data. The paper outlines all the advantages and disadvantages of Data Visualization tools and recommends to use the one which outclasses the comparison test. The later part of paper explains about the methodology proposed using Big Data Hadoop and CDH's Apache Impala, Hue, and Hive. The dataset chosen is imputed and fed to the Cloudera Engine for query processing and report generation. Further, the generated 2D output is given as input to Unity 3D engine for generating QR codes and 3D visualization using Marker-based technique of augmented reality.