Unlocking the potential of big data and analytics significance, applications in diverse domains and implementation of Apache Hadoop map/reduce for citation histogram
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2025.16.spl-2.11Keywords:
Big Data analytics, Hadoop, MapReduce, NameNodes, Jobtracker, Tasktracker, Hadoop ecosystem, Citation histogramDimensions Badge
Issue
Section
License
Copyright (c) 2025 The Scientific Temper

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Big Data analytics helps every sector who wants to grow. This paper also presents analysis of Big Data case studies in diverse domains. Various domains include supply chain, academics, India’s unique identification project, the digital India program and the project smart cities, in medical improved health care. Paper presents how Walmart Inc. a global retail chain offering a wide range of products, including groceries, apparel, and financial services, leverages Big Data analytics, processing 2.5 petabytes of data every hour, to enhance sales by predicting customer needs and optimizing product availability across its stores and how Oracle, committed to help people discover insights and unlock possibilities through data, showcases case studies in manufacturing that use predictive maintenance to enhance operational efficiency, production optimization, and product development. Additionally, Oracle’s Big Data solutions improve customer experience by analyzing data from mobile applications, purchases in stores, and various geographic locations to enhance selling and motivate purchase completion. Research paper presents Big Data, its characteristics, use of Hadoop to handle Big Data challenges and how it is better than typical distributed systems and RDBMS. It also explains how Hadoop’s HDFS and MapReduce work. It also gives Apache Hadoop’s installation instructions and demonstrates running of citation Histogram MapReduce program. It also discusses the Hadoop Ecosystem. Paper contributes for everyone who wants to work in the field of Big Data along with hands-on practical implementation, researchers can use different data and derive useful results.Abstract
How to Cite
Downloads
Similar Articles
- Olivia C. Gold, Jayasimman Lawrence, Enhanced LSTM for heart disease prediction in IoT-enabled smart healthcare systems , The Scientific Temper: Vol. 15 No. 02 (2024): The Scientific Temper
- Prem Yadav, Prashant Kumar, CLIMATE CHANGE AND BIODIVERSITY IN NARAYANI RIVER ECOSYSTEM AND ECOSYSTEM SERVICES , The Scientific Temper: Vol. 9 No. 1&2 (2018): The Scientific Temper
- Avdhesh Kumar, Manoj Agarwal, Studies on challenges and opportunities for foreign direct investment in the automobile industry in India , The Scientific Temper: Vol. 14 No. 02 (2023): The Scientific Temper
- J. M. Aslam, K. M. Kumar, Enhancing security of cloud using static IP techniques , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- S. Dhivya, S. Prakash, Power quality assessment in solar-connected smart grids via hybrid attention-residual network for power quality (HARN-PQ) , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
- A. Sathya, M. S. Mythili, MOHCOA: Multi-objective hermit crab optimization algorithm for feature selection in sentiment analysis of Covid-19 Twitter datasets , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- Amanda Q. Okronipa, Jones Y. Nyame, Adoption of health information systems in emerging economies: Evidence from Ghana , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- K. Mohamed Arif Khan, A.R. Mohamed Shanavas, Energy efficient techniques for iot application on resource aware fog computing paradigm , The Scientific Temper: Vol. 16 No. 02 (2025): The Scientific Temper
- C. Muruganandam, V. Maniraj, A Self-driven dual reinforcement model with meta heuristic framework to conquer the iot based clustering to enhance agriculture production , The Scientific Temper: Vol. 15 No. 02 (2024): The Scientific Temper
- N. Saranya, M. Kalpana Devi, A. Mythili, Summia P. H, Data science and machine learning methods for detecting credit card fraud , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
<< < 1 2 3 4 5 6 7 8 9 10 > >>
You may also start an advanced similarity search for this article.

