Developing Data Workflows: From Conceptual Blueprints to Physical Implementation

Bruno Oliveira () and Óscar Oliveira
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Bruno Oliveira: CIICESI, School of Management and Technology, Porto Polytechnic, 4610-156 Felgueiras, Portugal
Óscar Oliveira: CIICESI, School of Management and Technology, Porto Polytechnic, 4610-156 Felgueiras, Portugal

Data, 2025, vol. 10, issue 7, 1-27

Abstract: Data workflows are an important component of modern analytical systems, enabling structured data extraction, transformation, integration, and delivery across diverse applications. Despite their importance, these workflows are often developed using ad hoc approaches, leading to scalability and maintenance challenges. This paper proposes a structured, three-level methodology—conceptual, logical, and physical—for modeling data workflows using Business Process Model and Notation (BPMN). A custom BPMN metamodel is introduced, along with a tool built on BPMN.io, that enforces modeling constraints and supports translation from high-level workflow designs to executable implementations. Logical models are further enriched through blueprint definitions, specified in a formal, implementation-agnostic JSON schema. The methodology is validated through a case study, demonstrating its applicability across ETL and machine learning domains, promoting clarity, reuse, and automation in data pipeline development.

Keywords: data workflows; data pipelines; conceptual modeling; BPMN; data integration; logical modeling; physical implementation; logical blueprints (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2025
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