Key Technologies and Methods for Building Scalable Data Lakes

Registration ID: IJNRD_226553

Published ID: IJNRD2207179

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SHANMUKHA EETI, , SHALU JAIN,, DR. POORNIMA TYAGI,

Keywords: Data lakes, scalability, big data, cloud-based solutions, distributed storage, Apache Hadoop, Apache Spark, AWS, Azure, data ingestion, storage optimization, metadata management, data governance, data-driven decision-making.

Abstract: In the era of big data, organizations face the challenge of efficiently storing, processing, and analyzing vast amounts of data. Data lakes have emerged as a solution to address these needs, offering a flexible and scalable architecture for managing diverse data types. This paper explores the key technologies and methods essential for building scalable data lakes, focusing on the integration of cloud-based solutions, distributed storage systems, and advanced data processing frameworks. It discusses the role of technologies such as Apache Hadoop, Apache Spark, and cloud platforms like AWS and Azure in enhancing data lake performance and scalability. Furthermore, the paper examines best practices for data ingestion, storage optimization, and metadata management to ensure efficient data retrieval and governance. By analyzing case studies and real-world implementations, this study provides insights into the benefits and challenges of deploying scalable data lakes in various industries. The findings aim to guide organizations in leveraging data lakes to unlock the potential of big data, facilitating data-driven decision-making and innovation.

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SHANMUKHA EETI, , SHALU JAIN,, & DR. POORNIMA TYAGI, (July-2022). Key Technologies and Methods for Building Scalable Data Lakes. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 7(7), 1-21. https://ijnrd.org/papers/IJNRD2207179.pdf

Volume 7 Issue 7, July-2022

Pages : 1-21

Paper Reg. ID: IJNRD_226553

Published Paper Id: IJNRD2207179

Research Area: Engineering

Author Type: Indian Author

Country: GHAZIABAD, UP, India

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