The Shift to Cloud-Native Data Analytics: AWS, Azure, and Google Cloud Discussing the growing trend of cloud-native Big Data processing solutions

Authors

  • Naresh Dulam Vice President Sr Lead Software Engineer, JP Morgan Chase, USA Author

Keywords:

Cloud-native, data security, cloud providers

Abstract

The shift to cloud-native data analytics has rapidly emerged as a game-changing trend in the IT industry, fundamentally altering how organizations handle and analyze Big Data. As businesses increasingly turn to data-driven insights to make informed decisions and maintain a competitive edge, adopting cloud-native solutions has grown significantly. Cloud providers like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud have spearheaded this transformation by offering robust platforms designed to efficiently manage and process large-scale datasets. These cloud services allow businesses to store, analyze, and derive actionable insights from data without the burden of on-premises infrastructure. The benefits of moving to the cloud include scalability, flexibility, and cost-effectiveness, allowing businesses to scale their data processing capabilities up or down in response to changing needs. Cloud platforms also enable organizations to access advanced analytics tools and technologies without the need for extensive internal resources. However, this shift also comes with challenges. Data security remains a significant concern, as sensitive business and customer information is stored remotely. Integration with existing systems can be complex, particularly for organizations with legacy infrastructures, and ensuring proper data governance and compliance with regulatory standards becomes more critical than ever. In this context, AWS, Azure, and Google Cloud each offer unique solutions that address different aspects of cloud-native Big Data processing, from storage to analytics and machine learning. By evaluating the strengths and weaknesses of these platforms, businesses can make informed decisions on which cloud service best meets their needs while navigating the complexities of data security, integration, and governance. This article explores the advantages and challenges of cloud-native data analytics, shedding light on how organizations can leverage these platforms to unlock the full potential of their data while addressing potential risks.

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Published

08-02-2015

How to Cite

[1]
Naresh Dulam, “The Shift to Cloud-Native Data Analytics: AWS, Azure, and Google Cloud Discussing the growing trend of cloud-native Big Data processing solutions”, Distrib Learn Broad Appl Sci Res, vol. 1, pp. 28–48, Feb. 2015, Accessed: Dec. 23, 2024. [Online]. Available: https://dlabi.org/index.php/journal/article/view/217

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