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May 31, 2024INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT1 citationsOpen Access

Designing Efficient Data Pipelines: A Framework for Ingestion, Processing, and Enrichment

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Abstract

ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) pipelines are the foundation of modern data processing, enabling efficient transformation and integration of various data sources. Despite extensive research, significant gaps remain, particularly in the areas of data processing, data quality and integrity, and security and privacy. This article provides a comprehensive review of the existing literature on prompts to identify gaps. We then present the design and implementation of an advanced combination therapy system that addresses these issues. Our pipeline combines real-time data streaming, efficient data processing, and advanced security features. The results of this study help create efficient, reliable, and secure ETL/ELT processes and provide methods that organizations can use to optimize processes and improve survey results. Keywords—BigData, Pipeline, Extract-Transform-Load(ETL),

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A 2024 study studied this question.

synapsesocial.com/papers/68e6785bb6db64358760270ahttps://doi.org/10.55041/ijsrem35224
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Also Consider

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  1. 1A Conceptual Framework for Automating Data Pipelines Using ELT Tools in Cloud-Native Environments2021 · 1 citations
  2. 2THE ROLE OF ETL (EXTRACT-TRANSFORM-LOAD) PIPELINES IN SCALABLE BUSINESS INTELLIGENCE: A COMPARATIVE STUDY OF DATA INTEGRATION TOOLS2022 · 4 citations
  3. 3A Survey of Pipeline Tools for Data Engineering2024
  4. 4Key Challenges of Implementing ETL/ELT Processes and Methods to Overcome Them2025
  5. 5Big Data Pipeline: An Overview of Ingestion and Preparation Tools2025