Authors:
Noura Azaiez
1
and
Jalel Akaichi
2
Affiliations:
1
University of Tunis, Tunisia
;
2
King Khalid University, Saudi Arabia
Keyword(s):
Trajectory ELT Processes, Extraction, Loading, Transformation, Trajectory Construction, Trajectory Data Source Model, Trajectory Data Mart Model, Model Driven Architecture.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Business Process Management
;
e-Business
;
Enterprise Engineering
;
Enterprise Information Systems
;
Knowledge Management and Information Sharing
;
Knowledge-Based Systems
;
Languages, Tools and Architectures
;
Methodologies, Processes and Platforms
;
Model Transformation
;
Model Transformations and Generative Approaches
;
Model-Driven Architecture
;
Model-Driven Software Development
;
Models
;
Paradigm Trends
;
Software Engineering
;
Symbolic Systems
Abstract:
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 tran
sformation 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.
(More)