Algorithm and approaches to handle large Data- A Survey

TL;DR

This survey reviews algorithms and tools developed between 1994 and 2013 for managing and analyzing large-scale data across various fields, highlighting architectures suited for Big Data challenges.

Contribution

It compiles and analyzes a comprehensive set of algorithms and tools designed for handling Big Data, providing insights into their structures and applications.

Findings

Various algorithms for Big Data processing are identified and categorized.

Tools for analyzing large datasets are listed and compared.

Architectures suitable for Big Data management are discussed.

Abstract

Data mining environment produces a large amount of data, that need to be analyzed, patterns have to be extracted from that to gain knowledge. In this new era with boom of data both structured and unstructured, in the field of genomics, meteorology, biology, environmental research and many others, it has become difficult to process, manage and analyze patterns using traditional databases and architectures. So, a proper architecture should be understood to gain knowledge about the Big Data. This paper presents a review of various algorithms from 1994-2013 necessary for handling such large data set. These algorithms define various structures and methods implemented to handle Big Data, also in the paper are listed various tool that were developed for analyzing them.