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The model-Driven Architecture for the trajectory data Warehouse modeling

INTERNATIONAL JOURNAL OF data WAREHOUSING AND MINING 2020年第4期16卷 26-43页

作者： Azaiez, Noura Akaichi, Jalel Univ Tunis Inst Super Gest Bestmod Tunis Tunisia Univ Bisha Coll Comp & Informat Technol Dept Informat Syst Bisha Saudi Arabia

Business Intelligence includes the concept of data warehousing to support decision making. As the ETL process presents the core of the warehousing technology, it is responsible for pulling data out of the source systems and placing it into a data warehouse. Given the technology development in the field of geographical information systems, pervasive systems, and the positioning systems, the traditional warehouse features become unable to handle the mobility aspect integrated in the warehousing chain. Therefore, the trajectory or the mobility data gathered from the mobile object movements have to be managed through what is called the trajectory ELT. For this purpose, the authors emphasize the power of the model-driven architecture approach to achieve the whole transformation task, in this case transforming trajectory data source model that describes the resulting trajectories into trajectory data mart models. The authors illustrate the proposed approach with an epilepsy patient state case study.

关键词： Extraction Loading model-Driven Architecture trajectory data mart model trajectory data Source model trajectory ELT Process trajectory Reconstruction Transformation

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Override Traditional Decision Support Systems How trajectory ELT Processes modeling Improves Decision Making? 5

Override Traditional Decision Support Systems <i>How Traject...

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5th International Conference on model-Driven Engineering and Software Development (modelSWARD)

作者： Azaiez, Noura Akaichi, Jalel Univ Tunis Dept Comp Sci Inst Super Gest Tunis Tunisia King Khalid Univ Dept Comp Sci Coll Comp Sci Abha Saudi Arabia

ISBN: (纸本)9789897582103

Business Intelligence is often described as a set of techniques serving the transformation of raw data into meaningful information for business analysis purposes. Thanks to the technology development in the realm of Geographical Information Systems, the so-called trajectory data were appeared. Analysing these raw trajectory data coming from the movements of mobile objects requires their transformation into decisional data. Usually, the Extraction-Transformation-Loading (ETL) process ensures this task. However, it seems inadequate to support trajectory data. Integrating the trajectory aspects gives the birth of trajectory ETL process (T-ETL). Unfortunately, this is not enough. In fact, the business analysis main purpose is to minimize costs and time consuming. Thus, we propose to swap the T-ETL tasks scheduling: instead of transforming the data before they are written, the trajectory Extraction, Loading and Transformation (T-ELT) process leverages the target system to achieve the transformation task. In this paper, we rely on a set of powerful mechanisms to handle the complexity of each T-ELT task. Wherefore, an algorithm is dedicated to ensure the transformation of raw mobile object positions into trajectories and from there we highlight the power of the model-driven Architecture approach to transform the resulting trajectories into analytical data in order to perform the Business Intelligence goal.

关键词： trajectory ELT Processes Extraction Loading Transformation trajectory Construction trajectory data Source model trajectory data mart model model Driven Architecture

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