Research Article
Exploring the Correlation between Data Pipeline Quality and the Advantages of SQL-based Data Pipelines
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 186 - Issue 13 |
| Published: March 2024 |
| Authors: Ankush Ramprakash Gautam |
10.5120/ijca2024923497
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Ankush Ramprakash Gautam . Exploring the Correlation between Data Pipeline Quality and the Advantages of SQL-based Data Pipelines. International Journal of Computer Applications. 186, 13 (March 2024), 29-32. DOI=10.5120/ijca2024923497
@article{ 10.5120/ijca2024923497,
author = { Ankush Ramprakash Gautam },
title = { Exploring the Correlation between Data Pipeline Quality and the Advantages of SQL-based Data Pipelines },
journal = { International Journal of Computer Applications },
year = { 2024 },
volume = { 186 },
number = { 13 },
pages = { 29-32 },
doi = { 10.5120/ijca2024923497 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2024
%A Ankush Ramprakash Gautam
%T Exploring the Correlation between Data Pipeline Quality and the Advantages of SQL-based Data Pipelines%T
%J International Journal of Computer Applications
%V 186
%N 13
%P 29-32
%R 10.5120/ijca2024923497
%I Foundation of Computer Science (FCS), NY, USA
Abstract
This research paper thoroughly examines the use of SQL based data pipelines, in the public cloud setting. Conventional approaches to data pipelines often face issues with securing data engineering resources for projects leading to setbacks and potential project failures. By utilizing SQL based data pipeline solutions available in the market organizations can speed up the development of their data lakes. Efficiently extract transformed datasets to support achieving desired outcomes. This enables businesses to improve efficiency, make informed decisions and gain a competitive edge within their industries. The article explores the benefits of employing SQL based data pipeline tools. Sheds light on the challenges associated with methods of creating data pipelines. Our analysis provides insights, for professionals aiming to optimize their data pipeline processes and maximize the value derived from their data.
References
- Amazon Data Pipeline definition [Online] https://aws.amazon.com/what-is/data-pipeline/
- Wikipedia SAAS definition [Online] https://en.wikipedia.org/wiki/Software_as_a_service
- Wikipedia SQL definition [Online] https://en.wikipedia.org/wiki/SQL
- Wikipedia Snowflake definition [Online] https://en.wikipedia.org/wiki/Snowflake_Inc.
- Wikipedia DBT definition [Online] https://en.wikipedia.org/wiki/Data_build_tool
Index Terms
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