Leveraging Business Process Models for ETL Design

Wilkinson, Kevin; Simitsis, Alkis; Castellanos, Malú; Dayal, Umeshwar

doi:10.1007/978-3-642-16373-9_2

Cited by 33 publications

(41 citation statements)

References 13 publications

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“…This work enables the design developed in BPMN to be compatible across multiple tools and easy to extend to fit the requirements of a particular application. The BPMN approach was then adapted by [20][21][22] to construct a conceptual model of an ETL workflow.…”

Section: Bpmn-based Conceptual Modelmentioning

confidence: 99%

“…The work in [22] proposes a layered method that starts with business requirements and systematically converts a conceptual model into its semantically equivalent physical implementation. The entire method is based on the QoXsuit of quality metrics [23] to construct an optimal ETL workflow.…”

Section: Bpmn-based Conceptual Modelmentioning

confidence: 99%

“…The QoX metrics are considered during the design and development of ETL workflows ranging from quantitative to qualitative metrics (e.g., performance, recoverability, and freshness). [22] fill the gap between different stages (conceptual, logical, and physical) of an ETL workflow design. Once the conceptual design is expressed in BPMN, it is converted into XML to translate a conceptual design into its semantically equivalent logical model.…”

Section: Bpmn-based Conceptual Modelmentioning

confidence: 99%

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From conceptual design to performance optimization of ETL workflows: current state of research and open problems

Ali

Wrembel

2017

The VLDB Journal

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In this paper, we discuss the state of the art and current trends in designing and optimizing ETL workflows. We explain the existing techniques for: (1) constructing a conceptual and a logical model of an ETL workflow, (2) its corresponding physical implementation, and (3) its optimization, illustrated by examples. The discussed techniques are analyzed w.r.t. their advantages, disadvantages, and challenges in the context of metrics such as autonomous behavior, support for quality metrics, and support for ETL activities as user-defined functions. We draw conclusions on still open research and technological issues in the field of ETL. Finally, we propose a theoretical ETL framework for ETL optimization.

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Section: Bpmn-based Conceptual Modelmentioning

confidence: 99%

Section: Bpmn-based Conceptual Modelmentioning

confidence: 99%

Section: Bpmn-based Conceptual Modelmentioning

confidence: 99%

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From conceptual design to performance optimization of ETL workflows: current state of research and open problems

Ali

Wrembel

2017

The VLDB Journal

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“…The complexity and variability of data transformations has introduced an additional challenge to the efforts for providing a commonly accepted modeling notation for these data flows. Several works have proposed different ETL modeling approaches, either ad-hoc [99], or based on well-known modeling languages, e.g., UML in [92] or BPMN in [3,101]. However, these modeling approaches do not provide any automatable means for the design of an ETL process (i.e., Low automation).…”

Section: Automationmentioning

confidence: 99%

A Unified View of Data-Intensive Flows in Business Intelligence Systems: A Survey

Jovanovic

Romero

Abelló

2016

Lecture Notes in Computer Science

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Abstract. Data-intensive flows are central processes in today's business intelligence (BI) systems, deploying different technologies to deliver data, from a multitude of data sources, in user-preferred and analysisready formats. To meet complex requirements of next generation BI systems, we often need an effective combination of the traditionally batched extract-transform-load (ETL) processes that populate a data warehouse (DW) from integrated data sources, and more real-time and operational data flows that integrate source data at runtime. Both academia and industry thus must have a clear understanding of the foundations of dataintensive flows and the challenges of moving towards next generation BI environments. In this paper we present a survey of today's research on data-intensive flows and the related fundamental fields of database theory. The study is based on a proposed set of dimensions describing the important challenges of data-intensive flows in the next generation BI setting. As a result of this survey, we envision an architecture of a system for managing the lifecycle of data-intensive flows. The results further provide a comprehensive understanding of data-intensive flows, recognizing challenges that still are to be addressed, and how the current solutions can be applied for addressing these challenges.

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“…The rationale behind this metamodel is the characterization of the ETL process as a combination of two perspectives: (i) A control process, responsible of synchronizing the transformation flows; (ii) A data process, feeding the data warehouse from the data sources. In this way, designers are able to specify conceptual models of ETL processes together with the business process of the enterprise (Wilkinson, 2010). Furthermore, the model-driven approach has been customized from a generic data warehouse approach (Mazón & Trujillo, 2008) into a concrete implementation for the ETL component.…”

Section: Introductionmentioning

confidence: 99%