ITIS404 : Data Mining/Business Intelligence

Department

Department of Information Systems

Academic Program

Bachelor in Information Systems

Type

Elective

Credits

03

Prerequisite

ITGS228

Overview

This course will define the notion of Business Intelligence and its components. It will change the way students think about data and its role in business. The goal of the course is to examine how data mining technologies can be used to improve decision-making. The topics will be covered include, Introduction to data mining and data mining process (identify business problem, build mining database, prepare data for modelling, build and evaluate model); Predictive Modelling; Descriptive/ Unsupervised Data Mining; Data Mining for business applications; Data mining and electronic commerce, Data warehousing: concepts and techniques; Data Warehouse Architecture; Data Warehousing to improve decision-making in business. Mini Project.

Intended learning outcomes

Knowledge &understand

  • Teaching student the basic concepts of data mining
  • Teaching student how to use data mining techniques
  • The student be able to know the principles of data mining quality and ways to improve it.
  • Provide student logical thinking methods to solve data mining problem.

mental skills

  • Improve the ability to understand data mining and its role in business
  • To recognize different functions for data mining.
  • Improve the ability of thinking, criticism and comparison.
  • The student acquires new information and skills to mine complex data

Practical & professional skills

  • Student acquires the ability to complete data mining projects.
  • Student acquires scientific research skills and the use of Internet networks in performing various tasks.
  • To train the student on teamwork, develop the ability for comparison and employ it in creating, designing and producing various data mining activities.
  • Acquires student the ability to use various techniques and tools and employ them for data mining.

General and transferable skills

  • Acquires student effective oral and written communication skills.
  • The student should develop his hobbies and skills related to data mining.
  • Acquires student the skill of creating scientific reports capable of describing problems and give solutions.
  • The student acquires data mining skills by using different techniques.

Teaching and learning methods

  • Lectures
  • Problem-based learning (discussions)
  • Mini-projects

Methods of assessments

  • Midterm exam = 20
  • discussions = 15
  • Mini-projects (presentation and writing report) = 15
  • Final exam = 50

Course contents

  • Why Data Mining?
  • What Is Data Mining?
  • What Kind of Data Can Be Mined?
  • What Kinds of Patterns Can Be Mined?
  • What Technology Are Used?
  • What Kind of Applications Are Targeted?
  • Major Issues in Data Mining
  • What Kinds of Patterns Can Be Mined?
  • What Technology Are Used?
  • What Kind of Applications Are Targeted?
  • Major Issues in Data Mining
  • What Kinds of Patterns Can Be Mined?
  • What Technology Are Used?
  • What Kind of Applications Are Targeted?
  • Major Issues in Data Mining
  • Data & Data Pre-processing
  • Data Objects and Attribute Types
  • Basic Statistical Descriptions of Data
  • Data Visualization
  • Measuring Data Similarity and Dissimilarity
  • Data Quality
  • Major Tasks in Data Preprocessing
  • Data Cleaning
  • Data Integration
  • Data Reduction
  • Data Transformation and Data Discretization
  • Data Warehouse: Basic Concepts
  • Data Warehouse Modeling: Data Cube and OLAP
  • Data Warehouse Design and Usage
  • DBMS
  • Classification & concept
  • Classification & method
  • Cluster Analysis: Basic Concepts
  • Cluster Analysis: Partitioning Methods
  • Hierarchical Methods
  • Outlier and Outlier Analysis
  • Outlier Detection Methods
  • Mining Complex Types of Data
  • Other Methodologies of Data Mining
  • Data Mining Applications
  • Data Mining and Society
  • Data Mining Trends

Information Retrieval Systems (ITIS401)
Knowledge Management (ITIS402)
Data Mining/Business Intelligence (ITIS404)
Business Process Management (ITIS405)
Decision support system (ITIS406)
IS Innovation and New Technologies (ITIS407)
E-Government (ITIS408)
Physics (ITPH111)
Mathematics I (ITMM111)
Arabic language 1 (ITAR111)
Problem solving Technic (ITGS113)
Intro to Information Technology (ITGS111)
General English1 (ITEL111)
Mathematics II (ITMM122)
logic Circuit Design (ITGS126)
System Analysis and Design (ITGS124)
Introduction to Programming (ITGS122)
General English2 (ITEL122)
Arabic language 2 (ITAR122)
Introduction to Statistics (ITST211)
Object Oriented Programmin (ITGS211)
Introduction to Software Engineering (ITGS213)
Introduction to Networking (ITGS215)
Discrete Structures (ITGS217)
Numerical analysis (ITGS219)
Computer Architucture & Organization (ITGS223)
Data Structure (ITGS220)
Foundation of Information Systems (ITGS222)
Information Security (ITGS224)
Introduction to Internet Programming (ITGS226)
Introduction to database (ITGS228)
Operating System (ITGS302)
Scientific Writing (ITGS304)
Web Application Development (ITIS311)
Human Computer Interaction (ITIS312)
Data and Information Management (ITIS313)
Advanced Databases (ITIS325)
IT Infrastructure (ITIS323)
Design and Analysis algorithms (ITGS301)
Multimedia Systems (ITIS324)
Advanced System analysis & Design (ITIS326)
Enterprise Architecture (ITIS411)
Risk management and Security (ITIS412)
Introduction to Artificial Intelligence (ITIS413)
IT Project Management (ITGS303)
Enterprise Systems (ITIS421)
IS strategy ,management and acquisition (ITIS422)