# A Taxonomy on Big Data: Survey

**Authors:** Ripon Patgiri  
**arXiv:** [1808.08474](https://arxiv.org/abs/1808.08474)  
**Date:** 2018-08-25  
**Summary page:** https://www.summarizepaper.com/en/paper/1808.08474v3/

## Key points

- Big Data paradigm is popular in various fields such as science, engineering, economics, business, social science, and government
- Organizations use Big Data to enhance performance and generate revenue
- Numerous new technologies have emerged based on Big Data
- The paper titled "A Taxonomy on Big Data: Survey" presents a taxonomy of Big Data and provides insights into the paradigm
- Factors like IoT devices and smart technologies contribute to the exponential growth of Big Data in areas like healthcare, agriculture, transportation, etc.
- Sciences generate enormous datasets that require handling through Big Data techniques
- The taxonomy presented in the paper covers aspects of Big Data analytics including classification, security mining, and machine learning
- The taxonomy provides a comprehensive framework for understanding and organizing the vast amount of data generated
- The paper offers valuable insights into the world of Big Data and its impact on organizations across sectors
- It serves as a useful resource for researchers and practitioners working with large datasets.

## Summary

The Big Data paradigm has become incredibly popular in various fields such as science, engineering, economics, business, social science and government. Organizations are utilizing Big Data to enhance their performance by leveraging massive amounts of data. These data assets generate revenue for the organizations leading to the widespread adoption of Big Data strategies to boost revenue. As a result numerous new technologies have emerged based on Big Data. In this paper titled "A Taxonomy on Big Data: Survey," Ripon Patgiri presents a taxonomy of Big Data and provides an in-depth insight into the Big Data paradigm. The author discusses the exponential growth of Big Data due to factors like IoT devices and smart technologies in areas such as healthcare, agriculture, transportation and more. Additionally the paper explores how sciences generate enormous datasets that require handling through Big Data techniques. The taxonomy presented in the paper covers various aspects of Big Data analytics including classification, security mining and machine learning. By categorizing different elements within the realm of Big Data this taxonomy provides a comprehensive framework for understanding and organizing the vast amount of data generated. Overall this paper offers valuable insights into the world of Big Data and its impact on organizations across different sectors. It serves as a useful resource for researchers and practitioners seeking to navigate the complexities of working with large datasets and harnessing their potential for organizational growth and success.