SysML Based Conceptual ETL Process Modeling

Biswas, Neepa; Chattopadhyay, Samiran; Mahapatra, Gautam; Chatterjee, Santanu; Mondal, Kartick Chandra

doi:10.1007/978-981-10-6430-2_19

Cited by 12 publications

(7 citation statements)

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“…ETL process modeling proposals based on the UML standard modeling language were among the first attempts in this area of research [6,22,[33][34][35]. Although UML is the most popular modeling language, due to its wide range of uses in software system development and the succession of improvements it has undergone, it has advantages and drawbacks; as such, all modeling work based on this unified modeling language has advantages and limits.…”

Section: Etl Process Modeling Approaches Based On Umlmentioning

confidence: 99%

“…The proposal of [35] used a systems modeling language (SysML) requirement diagram and an activity diagram for the expression of ETL processes. SysML is a graphical modeling language derived from UML, with some additional facilities.…”

Section: Summary Of Etl Process Modeling Approaches Based On Umlmentioning

confidence: 99%

“…SysML is a graphical modeling language derived from UML, with some additional facilities. According to [35], the requirement diagram was used to support text-based requirements, their relationship, and test cases using graphical constructs. In contrast, the activity diagram is deployed to explore system behavior by showing the flow of control and data within activities.…”

Section: Summary Of Etl Process Modeling Approaches Based On Umlmentioning

confidence: 99%

“…Indeed, the works proposed by [6,22] were based on the class diagram to conceptually model the proposed ETL process. The works of [33,34,39] were based on the activity diagram, while [35,40] used both activity and requirement diagrams to express the requirements, based on the text and their relationship provided by the SysML. In addition, the only contribution that used the object diagram was that of [39].…”

Section: Comparison Of Uml-based Approachesmentioning

confidence: 99%

“…In this context, they shared sentiment with [39], in that these automatic transformations allow the designer to save time and effort in obtaining the final implementation of the ETL process. Another particularity of these research works is that they consider the "dynamic aspect" [33][34][35] by describing the process behavior during the modeling phase, often based on the activity diagram. Nevertheless, in terms of side mapping schema, only two research works proposed a mapping schema and a mapping diagram ( [6,22], respectively), to ensure the mapping between the data sources and the DW data storage schema.…”

Section: Comparison Of Uml-based Approachesmentioning

confidence: 99%

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Data Warehousing Process Modeling from Classical Approaches to New Trends: Main Features and Comparisons

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The extract, transform, and load (ETL) process is at the core of data warehousing architectures. As such, the success of data warehouse (DW) projects is essentially based on the proper modeling of the ETL process. As there is no standard model for the representation and design of this process, several researchers have made efforts to propose modeling methods based on different formalisms, such as unified modeling language (UML), ontology, model-driven architecture (MDA), model-driven development (MDD), and graphical flow, which includes business process model notation (BPMN), colored Petri nets (CPN), Yet Another Workflow Language (YAWL), CommonCube, entity modeling diagram (EMD), and so on. With the emergence of Big Data, despite the multitude of relevant approaches proposed for modeling the ETL process in classical environments, part of the community has been motivated to provide new data warehousing methods that support Big Data specifications. In this paper, we present a summary of relevant works related to the modeling of data warehousing approaches, from classical ETL processes to ELT design approaches. A systematic literature review is conducted and a detailed set of comparison criteria are defined in order to allow the reader to better understand the evolution of these processes. Our study paints a complete picture of ETL modeling approaches, from their advent to the era of Big Data, while comparing their main characteristics. This study allows for the identification of the main challenges and issues related to the design of Big Data warehousing systems, mainly involving the lack of a generic design model for data collection, storage, processing, querying, and analysis.

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