COURSE UNIT TITLE

: DATA WAREHOUSES AND BUSINESS INTELLIGENCE

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
CME 4434 DATA WAREHOUSES AND BUSINESS INTELLIGENCE ELECTIVE 2 2 0 6

Offered By

Computer Engineering

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

PROFESSOR DOCTOR RECEP ALP KUT

Offered to

Computer Engineering

Course Objective

Main goal of this course is to understand and implement classical models and algorithms in data warehousing. Students will learn how to analyze the data, identify the problems, and choose the relevant models and algorithms to apply. They will further be able to assess the strengths and weaknesses of various methods and algorithms and to analyze their behavior.

Learning Outcomes of the Course Unit

1   Learn about data warehouses.
2   Learn different DW modeling.
3   Learn the ETL processes.
4   Learn Business Intelligence.
5   Learn how to develop End User Applications in BI

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction
2 Basic concepts of Data Warehouse
3 Introduction to Data Mining
4 Data Preprocessing
5 Data Preprocessing
6 Clustering
7 Clustering
8 Classification
9 Classification
10 Validation
11 Association Rule Mining
12 Project Presentation
13 Project Presentation
14 Datawarehouse and Algorithms Topics Review

Recomended or Required Reading

Textbook: M. Golfarelli, S. Rizzi. Data Warehouse Design: Modern Principles and Methodologies. McGraw-Hill, 2009.
Supplementary Book:
R. Kimball, "The Data Warehouse Toolkit", 2nd edition.
W. H. Inmon, "Building the Data Warehouse", 3rd edition.

Planned Learning Activities and Teaching Methods

Presentation
Problem Solving
Project
Homework
Laboratory

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 ASG ASSIGNMENT
3 PRJ PROJECT
4 FCG FINAL COURSE GRADE MTE * 0.20 + ASG * 0.30 + PRJ * 0.50


Further Notes About Assessment Methods

None

Assessment Criteria

Midterm exam is 20 %, homeworkis %30, project is 50% of the course grade.

Language of Instruction

English

Course Policies and Rules

Participation is mandatory.

Contact Details for the Lecturer(s)

Prof. Dr. Alp KUT
alp@cs.deu.edu.tr
0232 3017405

Office Hours

Monday 13:00-15:00

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 2 28
Tutorials 14 2 28
Preparations before/after weekly lectures 14 2 28
Preparation for midterm exam 1 10 10
Preparation for final exam 1 10 10
Preparing presentations 1 2 2
Project Preparation 1 30 30
Final 1 2 2
Midterm 1 2 2
TOTAL WORKLOAD (hours) 140

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.1433
LO.243323
LO.34333
LO.4432
LO.543323

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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