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Main Authors: Rucco, Chiara, Saad, Motaz, Longo, Antonella
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2511.03393
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author Rucco, Chiara
Saad, Motaz
Longo, Antonella
author_facet Rucco, Chiara
Saad, Motaz
Longo, Antonella
contents Traditional ETL and ELT design patterns struggle to meet modern requirements of scalability, governance, and real-time data processing. Hybrid approaches such as ETLT (Extract-Transform-Load-Transform) and ELTL (Extract-Load-Transform-Load) are already used in practice, but the literature lacks best practices and formal recognition of these approaches as design patterns. This paper formalizes ETLT and ELTL as reusable design patterns by codifying implicit best practices and introduces enhanced variants, ETLT++ and ELTL++, to address persistent gaps in governance, quality assurance, and observability. We define ETLT and ELTL patterns systematically within a design pattern framework, outlining their structure, trade-offs, and use cases. Building on this foundation, we extend them into ETLT++ and ELTL++ by embedding explicit contracts, versioning, semantic curation, and continuous monitoring as mandatory design obligations. The proposed framework offers practitioners a structured roadmap to build auditable, scalable, and cost-efficient pipelines, unifying quality enforcement, lineage, and usability across multi-cloud and real-time contexts. By formalizing ETLT and ELTL, and enhancing them through ETLT++ and ELTL++, this work bridges the gap between ad hoc practice and systematic design, providing a reusable foundation for modern, trustworthy data engineering.
format Preprint
id arxiv_https___arxiv_org_abs_2511_03393
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Formalizing ETLT and ELTL Design Patterns and Proposing Enhanced Variants: A Systematic Framework for Modern Data Engineering
Rucco, Chiara
Saad, Motaz
Longo, Antonella
Databases
Traditional ETL and ELT design patterns struggle to meet modern requirements of scalability, governance, and real-time data processing. Hybrid approaches such as ETLT (Extract-Transform-Load-Transform) and ELTL (Extract-Load-Transform-Load) are already used in practice, but the literature lacks best practices and formal recognition of these approaches as design patterns. This paper formalizes ETLT and ELTL as reusable design patterns by codifying implicit best practices and introduces enhanced variants, ETLT++ and ELTL++, to address persistent gaps in governance, quality assurance, and observability. We define ETLT and ELTL patterns systematically within a design pattern framework, outlining their structure, trade-offs, and use cases. Building on this foundation, we extend them into ETLT++ and ELTL++ by embedding explicit contracts, versioning, semantic curation, and continuous monitoring as mandatory design obligations. The proposed framework offers practitioners a structured roadmap to build auditable, scalable, and cost-efficient pipelines, unifying quality enforcement, lineage, and usability across multi-cloud and real-time contexts. By formalizing ETLT and ELTL, and enhancing them through ETLT++ and ELTL++, this work bridges the gap between ad hoc practice and systematic design, providing a reusable foundation for modern, trustworthy data engineering.
title Formalizing ETLT and ELTL Design Patterns and Proposing Enhanced Variants: A Systematic Framework for Modern Data Engineering
topic Databases
url https://arxiv.org/abs/2511.03393