Big data: Issues, challenges, tools and Good practices

TLDR

Big data, characterized by volume, velocity, variety, variability, value, and complexity, demands new technologies and architectures, making traditional analysis methods inadequate and presenting significant challenges for organizations. This paper aims to introduce Big data technology, highlight its importance in the modern world, and review projects that are reshaping science and society. The authors discuss the challenges of adopting Big data, examine tools such as Hadoop, and detail the problems Hadoop currently faces. The study concludes by outlining best practices for effective Big data implementation.

Abstract

Big data is defined as large amount of data which requires new technologies and architectures so that it becomes possible to extract value from it by capturing and analysis process. Due to such large size of data it becomes very difficult to perform effective analysis using the existing traditional techniques. Big data due to its various properties like volume, velocity, variety, variability, value and complexity put forward many challenges. Since Big data is a recent upcoming technology in the market which can bring huge benefits to the business organizations, it becomes necessary that various challenges and issues associated in bringing and adapting to this technology are brought into light. This paper introduces the Big data technology along with its importance in the modern world and existing projects which are effective and important in changing the concept of science into big science and society too. The various challenges and issues in adapting and accepting Big data technology, its tools (Hadoop) are also discussed in detail along with the problems Hadoop is facing. The paper concludes with the Good Big data practices to be followed.