Data Warehousing Process Modeling from Classical Approaches to New Trends: Main Features and Comparisons
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, sever...
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MDPI AG
2022-08-01
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| Online Access: | https://www.mdpi.com/2306-5729/7/8/113 |
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| author | Asma Dhaouadi Khadija Bousselmi Mohamed Mohsen Gammoudi Sébastien Monnet Slimane Hammoudi |
| author_facet | Asma Dhaouadi Khadija Bousselmi Mohamed Mohsen Gammoudi Sébastien Monnet Slimane Hammoudi |
| author_sort | Asma Dhaouadi |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-09T04:33:47Z |
| format | Article |
| id | doaj.art-4334b65322ed455f9aaf59962fd980c3 |
| institution | Directory Open Access Journal |
| issn | 2306-5729 |
| language | English |
| last_indexed | 2024-03-09T04:33:47Z |
| publishDate | 2022-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Data |
| spelling | doaj.art-4334b65322ed455f9aaf59962fd980c32023-12-03T13:31:02ZengMDPI AGData2306-57292022-08-017811310.3390/data7080113Data Warehousing Process Modeling from Classical Approaches to New Trends: Main Features and ComparisonsAsma Dhaouadi0Khadija Bousselmi1Mohamed Mohsen Gammoudi2Sébastien Monnet3Slimane Hammoudi4RIADI Laboratory, University of Manouba, Mannouba 2010, TunisiaLISTIC Laboratory, University of Savoie Mont Blanc, France Annecy-Chambéry, 74940 Chambéry, FranceRIADI Laboratory, University of Manouba, Mannouba 2010, TunisiaLISTIC Laboratory, University of Savoie Mont Blanc, France Annecy-Chambéry, 74940 Chambéry, FranceERIS, ESEO-Grande Ecole d’Ingénieurs Généralistes, 49100 Angers, FranceThe 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.https://www.mdpi.com/2306-5729/7/8/113ETL processdata warehouseETL modelingBig DataUMLBPMN |
| spellingShingle | Asma Dhaouadi Khadija Bousselmi Mohamed Mohsen Gammoudi Sébastien Monnet Slimane Hammoudi Data Warehousing Process Modeling from Classical Approaches to New Trends: Main Features and Comparisons Data ETL process data warehouse ETL modeling Big Data UML BPMN |
| title | Data Warehousing Process Modeling from Classical Approaches to New Trends: Main Features and Comparisons |
| title_full | Data Warehousing Process Modeling from Classical Approaches to New Trends: Main Features and Comparisons |
| title_fullStr | Data Warehousing Process Modeling from Classical Approaches to New Trends: Main Features and Comparisons |
| title_full_unstemmed | Data Warehousing Process Modeling from Classical Approaches to New Trends: Main Features and Comparisons |
| title_short | Data Warehousing Process Modeling from Classical Approaches to New Trends: Main Features and Comparisons |
| title_sort | data warehousing process modeling from classical approaches to new trends main features and comparisons |
| topic | ETL process data warehouse ETL modeling Big Data UML BPMN |
| url | https://www.mdpi.com/2306-5729/7/8/113 |
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