International Journal of Contemporary Research in Multidisciplinary

IJCRM Journal Metrics
No. of Volumes	4
No. of Issues	131
No. of Submissions	464
No. of Published Papers	494
Acceptance	31-40 Days
Review Papers	239
Research Papers	235
No. of Editor-in-Chief	0
No. of Editors/Reviewers	46
No. of Paper Downloads	107317
No. of Paper Views	809816

IJCRM Journal Metrics

Journal Established Year

Nov. 2022

No. of Volumes

No. of Issues

131

No. of Submissions

464

No. of Published Papers

494

Acceptance

31-40 Days

Review Papers

239

Research Papers

235

No. of Editor-in-Chief

No. of Editors/Reviewers

No. of Paper Downloads

107317

No. of Paper Views

809816

International Journal of Contemporary Research In Multidisciplinary, 2024;3(5):41-43

Leveraging big data to improve AI Operational Efficiency

Author Name: Jalagangamma; Dr. Nirvikar Katiyar;

1. Research Scholar, Sunrise University, Alwar, Rajasthan, India

2. Professor, Sunrise University, Alwar, Rajasthan, India

Paper Type: research paper

Article Information

Paper Received on: 2024-06-09

Paper Accepted on: 2024-07-06

Paper Published on: 2024-09-03

Abstract:

In the modern era, the convergence of Big Data and Artificial Intelligence (AI) is reshaping industries by enhancing operational efficiency. This paper explores how leveraging Big Data analytics can optimize AI performance, discussing methodologies, technologies, and case studies that demonstrate improvements in AI operational efficiency. The focus is on the integration of Big Data tools with AI systems, the benefits of real-time data processing, and the challenges faced in implementation.

Keywords:

Big Data Analytics, Artificial Intelligence Optimization, Real-Time Data Processing, Machine Learning Integration, Data Scalability

How to Cite this Article:

Jalagangamma,Dr. Nirvikar Katiyar. Leveraging big data to improve AI Operational Efficiency. International Journal of Contemporary Research in Multidisciplinary. 2024: 3(5):41-43

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