Implementing data warehousing solution in Google Cloud Using Big Query
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Keywords

BigQuery, Google Cloud, SQL, warehousing solution, data management, data security

How to Cite

[1]
Venkata Soma, “Implementing data warehousing solution in Google Cloud Using Big Query”, N. American. J. of Engg. Research, vol. 3, no. 1, Mar. 2022, Accessed: Nov. 27, 2024. [Online]. Available: http://najer.org/najer/article/view/31

Abstract

This study focused on assessing the effect of implementing a data warehousing solution in Google Cloud using BigQuery. This study shows the BigQuery architecture, which is based on the separation of storage and processing. The data is kept in a replicated, dependable, and distributed storage system, with elastic distributed compute nodes handling data input and processing. BigQuery proved to be a dependable, user-friendly, and customisable platform for extracting structured data from blockchains. The analysis yielded results in minutes to hours. BigQuery offers significant SQL capabilities, which will help the NY Mets or any other sports business to keep their secret information

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Copyright (c) 2022 North American Journal of Engineering Research

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