Educational Data Mining (EDM) is a method to
support learning and teaching processes. Educational
Intelligence (EI) is not wide spreading like a business
Intelligence (BI). Data Warehouse (DW) technology aims to
collect historical data from different kinds of Database (DB)
and unifies them under single schema by using the most
powerful tool as OLAP which helps the decision maker to
make a right decision. Educational Intelligence system
combines Educational records of students from two different
sources in a single DW. The inputs of educational data
warehouse can be in any format (such as reports...). Since
the quantities are huge, they are almost meaningless, on the
other hand the outputs mainly consist of reports and
flowcharts and KPIs with meaning and effective factor for
decision maker. The proposed DW is implemented based on
two simulated databases of Computer Science Department
in the College of Science, University of Basra for the last ten
years and AL_IRAQ University for the last 4 years
implemented by SQL Server 2014 and SQL Server Data
Tool (SSDT) 2012.
Published In:IJCSN Journal Volume 5, Issue 5
Date of Publication : October 2016
Pages : 824-827
Figures :05
Tables :--
Zina A. S. Abdullah : Computer Science, University of Basra, Iraq.
Taleb A. S. Obaid : College of Information Technology , University of Basra, Iraq.
Data Warehouse, Educational, OLAP System
This paper described design and implementation of a
successful educational data warehouse for higher
education at the University of Basra. Data warehousing
technology helps to collect historical huge data from
several kinds of databases and unify them under unified
schema in order to be used by on line Analytical
Processing (OLAP) to help lecturer and decision makers.
Extract, Transform and Load (ETL) system is the core of
the DW. Each type of data base needs different
constriction of ETL system according to the data types.
OLAP is the storage of multidimensional, generally
hierarchical, data providing near constant-time answers to
queries. The OLAP techniques can be utilized to obtain
students’ achievements and to perform descriptive
analysis. Decision Support System (DSS) technique and
algorithm can be applied in order to forecast potential
areas of studies for the students. The proposed designed
approach might be implemented by the lecturers and
heads of the departments and the decision makers.
[1] Subotic, Danijela, Patrizia Pošcic, and Vanja
Slavuj. "OlAP Tools in Education." Media, Culture
and Public Relations 4, no. 1 (2013): 34-44.
[2] Pinar, B. "A Comparison of Data Warehouse
Design Models." PhD diss., Master Thesis, Atilim
University, 2005.
[3] Reddy, G. Satyanarayana, Rallabandi Srinivasu, M.
Poorna Chander Rao, and Srikanth Reddy Rikkula.
"Data Warehousing, Data Mining, OLAP and OLTP
Technologies are essential elements to support
decision-making process in industries."
International Journal on Computer Science and
Engineering 2, no. 9 (2010): 2865-2873.
[4] Kimball, Ralph, and Margy Ross. "The Data
Warehouse Toolkit: The Complete Guide to
Dimensional Modeling". John Wiley & Sons, 2011.
[5] Mirabedini, Shirin. "Design of Flexible Mining
Language on Educational Analytical DataBase."
(2014).
[6] Zorrilla M.2009. Marta E. Zorrilla, “Data
Warehouse Technology for E-Learning”, Springer-
Verlag Berlin Heidelberg 2009.
