Re-engineering Enterprises Using Data Warehouse as a Driver and Requirements as an Enabler

Truong, Thai-Minh; Lê, Lam-Son; Ton, Long-Phuoc

doi:10.1109/edoc.2017.18

Cited by 5 publications

(3 citation statements)

References 15 publications

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“…However, this work does not demonstrate its feasibility because it does not provide a supporting tool. Truong et al 38 proposed a method that combines "enterprise's strategy together with data mining rules extracted from the data warehouse of the enterprise in order to make design-time changes to its business processes." This method tries to discard redundant tasks and reorder some business process tasks inefficiently located.…”

Section: Related Workmentioning

confidence: 99%

“…However, this work does not demonstrate its feasibility because it does not provide a supporting tool. Truong et al 38 proposed a method that combines “enterprise's strategy together with data mining rules extracted from the data warehouse of the enterprise in order to make design‐time changes to its business processes.” This method tries to discard redundant tasks and reorder some business process tasks inefficiently located. The idea of this realignment approach, according to the authors, is “to combine yesterday's behavioural facts (i.e., mining enterprise's operational data) with today's operationalization possibilities (e.g., goals), which results in tomorrow's business model.” Werf et al 39 also consider operational data for extracting architectural descriptions in which quality attributes are considered apart from functional aspects.…”

Section: Related Workmentioning

confidence: 99%

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ArchiRev—Reverse engineering of information systems toward ArchiMate models. An industrial case study

Pérez‐Castillo

Caivano

Ruíz

et al. 2020

J Software Evolu Process

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In the context of digital transformation, companies are increasingly forced to develop, manage and continually align IT and business. Companies have found in Enterprise Architecture (EA) a valuable tool to represent and manage IT and business in a holistic way by establishing connections among technology concerns and business/strategical/motivational ones. EA modelling is one of the most critical tasks in this context to represent accurate models that make the difference in the decision-making and governance processes of the company. In most of the cases, EA models are manually defined by experts which is usually error-prone and time-consuming. Thus, the constant business and IT realignment through manual modelling becomes complex and expensive. This research presents ArchiRev, an extensible reverse engineering method that automate the extraction of EA models (using ArchiMate language) by analysing different information systems artefacts. This proposal has been validated through an industrial case study in the context of a C#-based system of an Italian ship refurbishment company. The study has demonstrated the effectiveness (based in the opinion of some business experts) and efficiency of the method. The main implication is that EA modelling can be accelerated, whereas subjectivity and errors introduced by experts might be reduced.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

ArchiRev—Reverse engineering of information systems toward ArchiMate models. An industrial case study

Pérez‐Castillo

Caivano

Ruíz

et al. 2020

J Software Evolu Process

View full text Add to dashboard Cite

show abstract

“…It is crucial to track changes and to propagate them in the enterprise model upon receiving a change request. We find this feasible based on our previous work on verified design of the SeamCAD tool [38], our recent work on enterprise re-engineering [39], and a framework of ours that supports change propagation for enterprise models expressed in the SeamCAD visual language [40]. Layout and diagramming techniques should be extended to incorporate our change propagation framework.…”

Section: Final Considerationsmentioning

confidence: 99%

Diagramming Multi-Level Service-Oriented Enterprise Architecture

Lê

2019

SN COMPUT. SCI.

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Today's enterprise architecture should incorporate high-level enterprise services that are considered as wrappers of business processes and ICT capabilities. This service-oriented enterprise model consists of a large number of model elements capturing various aspects of the enterprise in question, making any attempt to browse it too cumbersome. Enterprise architecture modeling, therefore, often resorts to a multi-view representation where views are focused and scoped. We define a visual modeling language and develop a supporting tool called SeamCAD that together lay the foundation for further multi-level enterprise modeling techniques. This article is dedicated to our tool realizing a notation schema and reinforcing a distinctive diagramming layout designed to visually capture the hierarchical containment in enterprise models. We demonstrate our real-life EA applications that were constructed thanks to SeamCAD. We report users' feedback on SeamCAD.

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A method for transforming knowledge discovery metamodel to ArchiMate models

et al. 2021

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Enterprise architecture has become an important driver to facilitate digital transformation in companies, since it allows to manage IT and business in a holistic and integrated manner by establishing connections among technology concerns and strategical/motivational ones. Enterprise architecture modelling is critical to accurately represent business and their IT assets in combination. This modelling is important when companies start to manage their enterprise architecture, but also when it is remodelled so that the enterprise architecture is realigned in a changing world. Enterprise architecture is commonly modelled by few experts in a manual way, which is error-prone and time-consuming and makes continuous realignment difficult. In contrast, other enterprise architecture modelling proposal automatically analyses some artefacts like source code, databases, services, etc. Previous automated modelling proposals focus on the analysis of individual artefacts with isolated transformations toward ArchiMate or other enterprise architecture notations and/or frameworks. We propose the usage of Knowledge Discovery Metamodel (KDM) to represent all the intermediate information retrieved from information systems’ artefacts, which is then transformed into ArchiMate models. Thus, the core contribution of this paper is the model transformation between KDM and ArchiMate metamodels. The main implication of this proposal is that ArchiMate models are automatically generated from a common knowledge repository. Thereby, the relationships between different-nature artefacts can be exploited to get more complete and accurate enterprise architecture representations.

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Re-engineering Enterprises Using Data Warehouse as a Driver and Requirements as an Enabler

Cited by 5 publications

References 15 publications

ArchiRev—Reverse engineering of information systems toward ArchiMate models. An industrial case study

ArchiRev—Reverse engineering of information systems toward ArchiMate models. An industrial case study

Diagramming Multi-Level Service-Oriented Enterprise Architecture

A method for transforming knowledge discovery metamodel to ArchiMate models

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