Big Data Analytics in Cloud – Comparative Study |
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| © 2023 by IJCTT Journal | ||
| Volume-71 Issue-12 |
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| Year of Publication : 2023 | ||
| Authors : Naresh Kumar Miryala, Divit Gupta | ||
| DOI : 10.14445/22312803/IJCTT-V71I12P107 | ||
How to Cite?
Naresh Kumar Miryala, Divit Gupta, "Big Data Analytics in Cloud – Comparative Study," International Journal of Computer Trends and Technology, vol. 71, no. 12, pp. 30-34, 2023. Crossref, https://doi.org/10.14445/22312803/IJCTT-V71I12P107
Abstract
In the dynamic landscape of information technology, the convergence of Big Data Analytics and Cloud Computing stands out as a powerful paradigm reshaping the way organizations extract insights from massive datasets. This abstract encapsulates the essence of Big Data Analytics in the cloud, illustrating its broad significance and impact. It also highlights the inherent advantages of leveraging cloud infrastructure for Big Data Analytics, including scalability, flexibility, and cost-effectiveness. However, it acknowledges the challenges related to privacy, security, and ethical considerations in handling large datasets. By providing a general overview, this abstract aims to convey the transformative potential of integrating Big Data Analytics with Cloud Computing, ushering in a new era of data-driven innovation and insights. In a world where data is abundant and diverse, the scalability and flexibility offered by cloud platforms enable efficient storage, processing, and analysis of vast datasets. This abstract highlights the significance of leveraging cloud infrastructure for Big Data Analytics, facilitating real-time insights, informed decision-making, business intelligence, optimizing healthcare practices, and revolutionizing financial strategies and innovation. The paper addresses the synergy between Big Data and the cloud, emphasizing the role of distributed computing and parallel processing in handling large volumes of information.
Cloud computing emerges as a potent technology for large-scale and intricate computing, offering a solution that negates the need to maintain costly hardware, dedicated space, and software infrastructure. The growth in the volume of data, often referred to as Big Data facilitated by cloud computing, has been substantial. The research also investigates challenges related to scalability, availability, data integrity, transformation, quality, heterogeneity, privacy, legal and regulatory matters, and governance. Additionally, the paper delves into various Big Data processing techniques from both system and application perspectives, presenting a structured overview of challenges faced by application developers and database management system (DBMS) designers in developing and deploying internet-scale applications. Big Data Analytics in the Cloud represents a paradigm shift in the way organizations handle and derive value from massive datasets. This abstract explores the convergence of Big Data Analytics with cloud computing, showcasing its transformative impact on businesses across various sectors. It also discusses the challenges and opportunities associated with this integration, including considerations of data security, privacy, and the ethical use of analytics. By examining the broader implications, this abstract aims to provide a general understanding of the dynamic intersection between Big Data Analytics and cloud technologies, driving advancements in the data-driven landscape.
Keywords
Cloud Computing, Big Data, Data Processing, Data Analysis, Data Management, Data Privacy, Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS), Structured Data, Semi-Structured Data, Unstructured Data, Snowflake, Google Bi Query, MySQL Heatwave, Amazon Redshift.
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