Basics of Data Science

Authors

  • Dr. D. Hema Latha
  • Azmath Mubeen
  • Dr. D. Rama Krishna Reddy

Abstract

In this present era of big data Hadoop, cloud and other frameworks are available for huge data storage, now the concentration is on huge data processing. With the help of machine learning tools, techniques and algorithms, huge data processing can be done and AI can be implemented in machines and make the machines to function like human brain intelligence.

With the huge rise in data, there is a continual requirement for analyzing such a huge amount of data. Data Science concept can handle this data and develop useful machine learning models that predict the future results. Data Science is emerging multidisciplinary field with roots in mathematics, statistics, and computer science. Data science can be applied to wide range of applications such as business, finance, healthcare, transportation etc., as it can perform data extraction, data analysis, data visualization, and also manages huge amounts of data. The main objective of Data Scientists is to recognize and utilize relevant and important insights from data, so that it can be helpful for organizations in taking smarter decisions. During this process, different tools and methods to identify redundant patterns and hidden knowledge within the data can be used. Most efficient algorithms, powerful hardware and programming systems to solve the data related problems are also used.

This paper focuses on basics of Data Science and its implementation with a simple case study. Understanding and implementing data science can upgrade individual knowledge, skills and business.

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Published

2021-10-12