This document outlines a seminar presentation on big data and cloud computing. The presentation will discuss the methodology and implementation of using big data and cloud computing, including data ingestion from various sources, processing data in cloud tools, and ensuring data security, privacy and cost management. It will also explore applications of big data and cloud computing in various industries like media, IoT, government and e-commerce. The presentation aims to address the complexities and opportunities at the intersection of big data and cloud computing.

1. Bhujbal Knowledge City
MET Institute of Engineering
Title of Seminar
(Big Data with Cloud Computing: Discussions and
Challenges)
Presented By :-
Roll No - Full Name
Guided By –
Department of Information Technology
04 - Harshal Gorakh Bhoir
Dr S V Gumaste

2. Contents :
1. Introduction
2. Literature Survey
3. Methodology and Implementation
4. Results discussed if any
5. Applications
6. Conclusion
7. References
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3. Introduction :
In today's data-driven world, "Big Data with Cloud Computing" has
emerged as a powerful combination. Big data refers to vast and complex
datasets, while cloud computing offers scalable and cost-effective
infrastructure. Together, they enable organizations to unlock insights,
streamline operations, and address the challenges and opportunities in
the digital age.
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7. Literature Survey :
(Add Reference papers survey in table format. You can add Columns if required. 4-5
papers are expected for literature survey.)
Author name [Reference No.] Limitations
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8. Methodology and Implementation :
The methodology and implementation of "Big Data with Cloud
Computing: Discussions and Challenges" involve data
ingestion from various sources, data processing in cloud-
based tools, storage, and real-time analytics. Data security,
compliance, and cost management are priorities, ensuring
data privacy and efficient resource utilization. Governance
policies maintain data quality, and a focus on skills and
training sustains a skilled workforce. Strategies mitigate
vendor lock-in risks. This comprehensive approach addresses
the complexities and opportunities at the intersection of big
data and cloud computing, fostering data-driven decision-
making while harnessing scalability, security, and cost-
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9. Methodology:
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11. Implementation :
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13. Results discussed if any :
(Add proposed system results here.)
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14. Applications :
 Media and Entertainment:
 IoT and Smart Cities
 Social Media and Online Marketing
 Government and Public Services:
 E-commerce Application :
 Backup and Recovery Cloud service
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15. Conclusion :
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16. References :
1. Huang, G. B., Zhu, Q. Y., and Siew, C. K. (2004). “Extreme Learning Machine: a New Learning Scheme of Feedforward Neural Networks,” in Proceedings of
the 2004 IEEE international joint conference on neural networks (IEEE Cat. No. 04CH37541), Budapest, Hungary, July 2004 (IEEE), 985–990.
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17. Thank You …
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