Prediction in OLAP Cube
Data warehouses are now offering an adequate solution for managing large volumes of data. Online analysis supports OLAP data warehouses in the process of decision support and visualization tools offer, structure and operation of data warehouse. On the other hand, data mining allows the extraction of knowledge with technical description, classification, explanation and prediction. It is therefore possible to better understand the data by coupling on-line analysis with data mining through a unified analysis process. Continuing the work of R. Ben Messaoud, where exploitation of the coupling of on-line analysis and data mining focuses on the description, visualization, classification and explanation, we propose extending the OLAP prediction capabilities. To integrate the prediction in the heart of OLAP, an approach based on automatic learning with regression trees is proposed in order to predict the value of an aggregate or a measure. We will try to express our approach using data from a service management reviews to know that it would be the average obtained by the students if we open a new module, for a department at a certain criterion.
Keywords: online analysis OLAP, data mining, multidimensional data cube, prediction, regression tree, \"What-If Analysis\".
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ABOUT THE AUTHORS
Abdellah Sair
PHD Student ‘integration of the prediction in Cube OLAP’ at the National School of Applied Sciences of Agadir Morocco in collaboration with the ERIC laboratory of university Lyon 2 France,
Erraha Brahim
(PHD), Ability Professor in Computer Science at the National School of Applied Sciences of Agadir And team member of the Laboratory of Industrial Engineering and Computer Science (LG2I), National School of Applied Sciences of Agadir, University Ibn Zohr Morocco.
Malika Elkyal
(PHD), Ability Professor in Applied Mathematics at the National School of Applied Sciences of Agadir And team member of the Laboratory of Industrial Engineering and Computer Science (LG2I), National School of Applied Sciences of Agadir, University Ibn Zohr Morocco.
Sabine Loudcher
(PHD), Ability Professor in Computer Science at the Department of Statistics and Computer Science of the University of Lyon 2, France. Since 2000, she has been a member of the Decision Support Databases research group within the ERIC laboratory.
Abdellah Sair
PHD Student ‘integration of the prediction in Cube OLAP’ at the National School of Applied Sciences of Agadir Morocco in collaboration with the ERIC laboratory of university Lyon 2 France,
Erraha Brahim
(PHD), Ability Professor in Computer Science at the National School of Applied Sciences of Agadir And team member of the Laboratory of Industrial Engineering and Computer Science (LG2I), National School of Applied Sciences of Agadir, University Ibn Zohr Morocco.
Malika Elkyal
(PHD), Ability Professor in Applied Mathematics at the National School of Applied Sciences of Agadir And team member of the Laboratory of Industrial Engineering and Computer Science (LG2I), National School of Applied Sciences of Agadir, University Ibn Zohr Morocco.
Sabine Loudcher
(PHD), Ability Professor in Computer Science at the Department of Statistics and Computer Science of the University of Lyon 2, France. Since 2000, she has been a member of the Decision Support Databases research group within the ERIC laboratory.
