Amazon Redshift: Performance Tuning and Optimization
|© 2023 by IJCTT Journal|
|Year of Publication : 2023|
|Authors : Amol Kulkarni|
|DOI : 10.14445/22312803/IJCTT-V71I2P107|
How to Cite?
Amol Kulkarni, "Amazon Redshift: Performance Tuning and Optimization," International Journal of Computer Trends and Technology, vol. 71, no. 2, pp. 40-44, 2023. Crossref, https://doi.org/10.14445/22312803/IJCTT-V71I2P107
Data is the lifeline for any enterprise in today's world. Exabytes of data are generated daily due to billions of transactions worldwide, social media, smartphones, and gaming apps use. It is most crucial for an enterprise not only to collect exabytes of data in the OLTP ERP System but also to analyze it for Decision making, predictive analysis, trend analysis and gain insights into business using the Data Warehouse OLAP System. With the advent of Cloud technology, it is possible to handle exabytes of data in cloud-based OLTP ERP systems and analyze it in cloud-based Data Warehouse OLAP Systems. There are various cloud-based data warehouse systems available in the market, but an enterprise has to choose the right system based on cost, integration with the OLTP ERP System, integration with existing business intelligence tools, security, scalability, data loading and query performance. This paper demonstrates how the Amazon Redshift performance optimization options made it the first choice for any enterprise to load huge amounts of data and provide it quickly for decision-making and analytic reporting purposes.
Amazon S3, AWS, Business Intelligence (BI), Cloud, Data warehouse, ETL, Machine Learning (ML), SQL.
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