Big Data Analytics, Processing Models, Taxonomy of Tools, V’s, and Challenges: State-of-Art Review and Future Implications

Abstract

In the current digital era, data is budding tremendously from various sources like banks, businesses, education, entertainment, etc. Due to its significant consequence, it became a prominent proceeding for numerous research areas like the semantic web, machine learning, computational intelligence, and data mining. For knowledge extraction, several corporate sectors depend on tweets, blogs, and social data to get adequate analysis. It helps them predict the customer’s tastes and preferences, optimize the usage of resources. In some cases, the same data creates complications that lead to a problem named as big data. To solve this, so many researchers have given various solutions. Based on literature analysis formulated 6-s simulation towards big data, detailed information about characteristics, a taxonomy of tools, and discussed various processing paradigms. No one tool can truly fit for all solutions, so this paper helps to make decisions smoothly by providing enough information and discussing major privacy issues and future directions.

Exploring the Impact of Big Data Analytics on Organizational Decision-Making and Performance: Insights from Pakistan's Industrial Sector

“…When integrating modules or using DBA processing tools, high-speed internet networking known as ETL/ELT is used. To transform unprocessed data into information, Hadoop, MapReduce, and memory management are used (Dasari & Kaluri, 2023). For statistical analysis of bid data, which may be employed in process calculation and managing the suggested alternatives, data can be applied using a variety of languages, including SQL, HIV, Pig, and R. Vertica, Greenplum, and IBM Nateza are just a few of the solutions that certain Vendors manage using various ways.…”