The Basics of Big Data and Security Concerns

The Basics of Big Data and Security Concerns

Sharvari C. Tamane (MGM's Jawaharlal Nehru Engineering College, India), Vijender K. Solanki (Institute of Technology and Science Ghaziabad, India) and Madhuri S. Joshi (MGM's Jawaharlal Nehru Engineering College, India)
Copyright: © 2019 |Pages: 12
DOI: 10.4018/978-1-5225-7501-6.ch001
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Abstract

The chapter is written on two important buildings, the basics of Big data and their security concern. The chapter is classifying in different sections. The chapter starts with the basic of big data and is concluded with security concern. The chapter is enriched with different category examples to make texts easy for author understanding. The chapter begins with the introduction of big data, their memory size followed by the examples. The chapter explains the category of big data in type of structured, semi-structured and unstructured data. The discussion on operational data service and big data application is also included to ensure the basic understanding to readers. The second portion of chapter which is based on security in big data. It's explaining the issues and challenges in big data. The section also focusing on the shift paradigm from cloud environment to big data environment changes and the problems encounter by organizations. The section discusses the framework issue and concluded with the necessity of understanding security in the big data, keeping in view of expansion of information technology infrastructure in the 21st century.
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Introduction

Big data is a buzzword used to describe and transfer a massive volume of structured and/or unstructured data into knowledge. It is so huge that it is very difficult to process it using traditional database and software techniques. Big data helps companies to improve the performances of their applications and make faster intelligent decisions. Big data refers to Petabytes or Exabytes of data consisting of more than Gigabytes to Terabytes of records of more than lac users, all from different sources. These sources may include: web, sales, customer contact center, social media, mobile data etc. One must be familiar with the other terms of data as shown in Table 1. Big data is always not referring to big volume of data but also refers to the technology that deals with the large amount of data and the infrastructure needed to store that data. When dealing with larger data sets organizations face difficulties in being able to capture, organize, manage and integrate big data as standard tools and procedures are not designed to search and analyze massive data sets. It may take so many minutes/days/years to transfer the data from one location to other. Businesses or enterprises expects more fast processing and transfer of data to perform different operations on it. Ninety percent of data currently available in the world is generated in last few years.

Table 1.
Bytes and bigger bytes
DataUnit SizeBinary Size
1 bitA binary digit-
8 bits1 byte or 10023
1024 bytes1 kilo bytes (1 KB) or 103210
1024 KB1 Mega Bytes (1MB) or 106220
1024 MB1 Giga Bytes (1 GB) or 109230
1024 GB1 Tera Bytes (1 TB) or 1012240
1024 TB1 Peta Bytes (1 PB) or 1015250
1024 PB1 Exa Bytes (1 EB) or 1018260
1024 EB1 Zetta Bytes (1 ZB) or 1021270
1024 ZB1 Yotta Bytes (1 YB) or 1024280
1024 YB1 Bronto Bytes (1 BB) or 1027290
1024 BB1 Geo Bytes or 10302100
………

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