IJCSN International Journal of Computer Science and Network, Volume 5, Issue 5, October 2016 ISSN (Online) : 2277-5420 www.IJCSN.org Impact Factor: 1.02 824 Design and Implementation of Educational Data Warehouse Using OLAP 1 Zina A. S. Abdullah, 2 Taleb A. S. Obaid 1 Computer Science, University of Basra, Iraq 2 College of Information Technology , University of Basra, Iraq Abstract - 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. Keywords – Data Warehouse, Educational, OLAP System. 1. Introduction Information is the key element of today's business. To obtain the information, first we have to collect data - facts, numbers or text relationships among data that give us information, then converted to knowledge. So, the reason of many business organizations collect and store huge amounts of data in different formats. But, there is a problem concerning how to obtain substantial meaning in historical huge mass of data and convert it into useful information. Business Intelligence (BI) systems and Online Analytical Processing (OLAP) tools can be the solution. Business Intelligence systems approach allow commerce institutes to separate huge and arranged information from different proveniences and transform them into useful data. [1] Data warehousing bolster a suitable methodology in changing over operational information into significant and solid data to help the procedure of basic leadership Furthermore, data warehousing bolster the premise for information investigation approach like data mining and multidimensional examination. Data warehousing process contains extraction of data from heterogeneous data sources, cleaning, filtering and transforming data into a common structure and storing data in a structure that is easily accessed and used for reporting and analysis purposes [2]. The goal of On-Line Logical Preparing (OLAP) instruments is systematic handling and information extraction with the end goal of basic leadership. With the guide of OLAP instruments, associations can precisely know the state inside the organization and all its parts, thinking about the states of the business. These tools can reveal hidden patterns in the collected data and, thus, help managers and analysts in making good decisions [3] Data warehouse is a gathering of choice bolster advances, aiding and qualifying the people who involved (official, administrator, and investigator) to improve production and more secure choices. It executes a real execution of a choice bolster information model and keeps the data on which an undertaking needs to create vital choices. The data can be kept in several kinds of databases. The "data warehouse "is one database design that has lately appeared, actually it is a store of multiple heterogeneous data sources, arranged in a systematic way under a