ESP Journal of Engineering & Technology Advancements |
© 2021 by ESP JETA |
Volume 1 Issue 1 |
Year of Publication : 2021 |
Authors : Abhilash Katari, Dinesh Kalla |
: 10.56472/25832646/ESP-V1I1P116 |
Abhilash Katari, Dinesh Kalla, 2021. "Cost Optimization in Cloud-Based Financial Data Lakes: Techniques and Case Studies", ESP Journal of Engineering & Technology Advancements 1(1): 150-157.
Managing costs in cloud-based financial data lakes is crucial for companies aiming to balance performance with budget constraints. In an era where data is a key asset, financial institutions must navigate the complexities of storing and processing vast amounts of information without overspending. This article delves into practical techniques for cost optimization in cloud-based financial data lakes, providing real-world case studies to illustrate successful implementations. We begin by exploring foundational strategies such as choosing the right cloud provider and leveraging cost-effective storage solutions like tiered storage and data compression. By understanding the nuances of pricing models and selecting appropriate services, organizations can significantly reduce their expenses. Additionally, we highlight the importance of effective data lifecycle management, including archiving seldom-used data and automating data deletion policies. The article also examines advanced techniques such as using serverless computing and containerization to optimize compute resources. These methods allow for scaling resources up or down based on demand, ensuring that companies only pay for what they use. Implementing cost monitoring and management tools is another key strategy, enabling real-time tracking of expenses and helping to identify potential savings opportunities. To bring these concepts to life, we present case studies from leading financial institutions that have successfully implemented these techniques. These examples demonstrate the tangible benefits of cost optimization, showcasing reduced operational costs, improved data processing efficiency, and enhanced overall financial performance. By adopting these strategies, other organizations can learn how to better manage their cloud-based financial data lakes, achieving a balance between cost and performance.
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Cloud-Based Financial Data Lakes, Cost Optimization, Resource Provisioning, Data Lifecycle Management, Automated Cost Monitoring, Serverless Architectures, Case Studies, Financial Institutions, Operational Efficiency, Cost Management.