Enhancing Scalability and Reliability of Batch Data Transformation Workflows Using Automation and Orchestration Tools Article Swipe
Moving data around in large volumes within big businesses is a natural happening of business nowadays. With this exponential growth, the need for more reliable, scalable, and effective batch data transformation techniques becomes increasingly important. As the need for data processing increases, so too has the complexity of managing and overseeing such systems. Automation and orchestration technologies as Apache Airflow and AWS Step Functions greatly help to maximize batch operations by automating job execution, managing problematic dependencies, and improving fault tolerance. Apache Airflow is perfect for very flexible, code-driven procedures with simplicity for complex data pipelines. Conversely, AWS Step Functions provide a serverless architecture with strong connection with the AWS environment, therefore enabling perfect scaling and robust error-handling capability. Together with research of how different technologies manage scalability, reliability, and dependency management—the main challenges with batch data transformation—are examined in this paper. Moreover, a comparison of their benefits and disadvantages guides businesses in choosing the technology most appropriate for their specific need. Discussed are best practices for implementation and future trends in workflow automation including the integration of machine learning, real-time monitoring, and multi-cloud installations, therefore providing a whole picture of the shifting terrain of data engineering.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.36948/ijfmr.2020.v02i06.22568
- OA Status
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- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4406614264Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.36948/ijfmr.2020.v02i06.22568Digital Object Identifier
- Title
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Enhancing Scalability and Reliability of Batch Data Transformation Workflows Using Automation and Orchestration ToolsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2020Year of publication
- Publication date
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2020-11-25Full publication date if available
- Authors
-
Varun GargList of authors in order
- Landing page
-
https://doi.org/10.36948/ijfmr.2020.v02i06.22568Publisher landing page
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://doi.org/10.36948/ijfmr.2020.v02i06.22568Direct OA link when available
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Orchestration, Workflow, Scalability, Automation, Computer science, Reliability (semiconductor), Transformation (genetics), Reliability engineering, Database, Engineering, Chemistry, Mechanical engineering, Power (physics), Gene, Art, Physics, Visual arts, Biochemistry, Quantum mechanics, MusicalTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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