Big Data Analytics: Tools, Technologies, and Real-World Applications – A Review

Elavarasi  Kesavan

doi:10.69968/ijisem.2024v3i3120-126

Authors

Elavarasi Kesavan Full Stack QA Architect, Cognizant https://orcid.org/0009-0008-3844-0286

DOI:

https://doi.org/10.69968/ijisem.2024v3i3120-126

Keywords:

Big Data Analytics (BDA), Data analysis, Cloud computing, Apache Hadoop, Data Mining, Natural Language Processing (NLP)

Abstract

The need for data analytics and storage has grown exponentially due to the Internet's and the digital economy's quick expansion, and IT departments are finding it very difficult to safeguard and analyze these larger amounts of data. Big Data analytics optimizes client retention and creates new business possibilities by gleaning value from these massive amounts of data. Examine the many studies on tools, methods, and practical applications of big data analytics in this page. It concluded that Big Data Analytics has revolutionized multiple sectors, particularly healthcare, by enabling real-time, data-driven decision-making. Leveraging tools like Hadoop, Map Reduce, and cloud computing, organizations can efficiently manage and analyze vast volumes of structured and unstructured data. Languages such as Python and R, along with techniques like text mining and machine learning, enhance data integration and insight generation. The COVID-19 pandemic highlighted the critical role of big data in driving smarter decisions across industries. As data continues to grow exponentially, Big Data Analytics remains central to innovation, operational efficiency, and informed strategies in the digital age.

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