International Journal of Contemporary Research in Multidisciplinary

IJCRM Journal Metrics
No. of Volumes	4
No. of Issues	144
No. of Submissions	476
No. of Published Papers	543
Acceptance	31-40 Days
Review Papers	260
Research Papers	262
No. of Editor-in-Chief	0
No. of Editors/Reviewers	46
No. of Paper Downloads	119350
No. of Paper Views	859664

IJCRM Journal Metrics

Journal Established Year

Nov. 2022

No. of Volumes

No. of Issues

144

No. of Submissions

476

No. of Published Papers

543

Acceptance

31-40 Days

Review Papers

260

Research Papers

262

No. of Editor-in-Chief

No. of Editors/Reviewers

No. of Paper Downloads

119350

No. of Paper Views

859664

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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