International Journal of Contemporary Research in Multidisciplinary

IJCRM Journal Metrics
No. of Volumes	3
No. of Issues	86
No. of Submissions	345
No. of Published Papers	308
Acceptance	31-40 Days
Review Papers	160
Research Papers	134
No. of Editor-in-Chief	0
No. of Editors/Reviewers	43
No. of Paper Downloads	55435
No. of Paper Views	456694

IJCRM Journal Metrics

Journal Established Year

Nov. 2022

No. of Volumes

No. of Issues

No. of Submissions

345

No. of Published Papers

308

Acceptance

31-40 Days

Review Papers

160

Research Papers

134

No. of Editor-in-Chief

No. of Editors/Reviewers

No. of Paper Downloads

55435

No. of Paper Views

456694

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

Leveraging big data to improve AI Operational Efficiency

Author Name: Jalagangamma; Dr. Satish Narayanrao Gujar;

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. Satish Narayanrao Gujar. Leveraging big data to improve AI Operational Efficiency. International Journal of Contemporary Research in Multidisciplinary. 2024: 3(5):41-43

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