Data Mining, Big Data, Data Analytics

Abstract

In this digital and computing world, data formation and collection rate are growing very rapidly. With these improved proficiencies of data storage and fast computation along with the real-time distribution of data through the internet, the usual everyday ingestion of data is mounting exponentially. With the continuous advancement in data storage and accessibility of smart devices, the impact of big data will continue to develop. This chapter provides the fundamental concepts of big data, its benefits, probable pitfalls, big data analytics and its impact in Bioinformatics. With the generation of the deluge of biological data through next generation sequencing projects, there is a need to handle this data trough big data techniques. The chapter also presents a discussion of the tools for analytics, development of a novel data life cycle on big data, details of the problems and challenges connected with big data with special relevance to bioinformatics.

Data Visualization of Big Data for Predictive and Descriptive Analytics for Stroke, COVID-19, and Diabetes

“…Sambyal et al (2019) categorized the steps of big data analytics as (a) collection, (b) storage, (c) processing, and (d) visualization, and they presented a list of tools and a description for each of the steps. Panigrahi and Singh (2017) presented a study on big data analytics in bioinformatics that includes the use of genetic algorithms, the development of a novel data life cycle on big data, and details and challenges connected with big data with special relevance to bioinformatics. Other related works about big data and healthcare include Borges do Nascimento (2021), Ranjan et al (2021), and Sweeney et al (2023).…”