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Monash University

FIT3003 Business intelligence and data warehousing - Semester 2, 2011

Automation and the use of technological tools have resulted in the accumulation of vast volumes of data by modern business organisations. Data warehouses have been set up as repositories to store this data and improved techniques now result in the speedy collection and integration of such data. OLAP technology has resulted in the faster generation of reports and more flexible analysis based on the data repositories. Business intelligence (BI) can be considered as the art of exploring and analysing this data, extracting relevant information and identifying patterns, and turning such information and patterns into knowledge upon which actions can be taken. This unit will explore the concepts of BI, including the emergence of BI and factors influencing BI, technology requirements for BI and will provide hands on experience on designing and building business intelligence systems.

Mode of Delivery

Clayton (Day)

Contact Hours

2 hrs lectures/wk, 2 hrs laboratories/wk

Workload

Students will be expected to spend a total of 12 hours per week during semester on this unit as follows:

  • 2 hour lecture and
  • 2 hour tutorial (or laboratory) (requiring advance preparation)
  • a minimum of 2 hours of personal study per 1 hour of contact time in order to satisfy the reading and assignment expectations.

Unit Relationships

Prerequisites

One of FIT1004, FIT2010, FIT1013, BUS1010, BUS3112, CSE2316, CSE3316

Chief Examiner

Dr Damminda Alahakoon

Campus Lecturer

Clayton

Damminda Alahakoon

Tutors

Clayton

Sumith Matharage

Contact hours: To be advised

Asanka Fonseka

Contact hours: To be advised

Viva Huang

Contact hours: To be advised

Academic Overview

Learning Objectives

At the completion of this unit students will have -

A knowledge and understanding of:

  • the role of Data Warehousing (DW) as opposed to operational databases;
  • the definition and the need of Business intelligence (BI);
  • DW development methodology;
  • dimensional models compared to ER models;
  • DW architectures, ETL and data quality issues;
  • how DW can support BI;
  • BI tools, techniques and OLAP;
  • Data Mining (DM) techniques;
  • Data Mining Tools.

Developed attitudes that enable them to:
  • recognise the value of DW and BI for a business organisation;
  • adapt a critical approach to DW and BI technology in a business context;
  • appreciate the value of DW for effective management support and decision making;
  • understand the importance and value of BI tool and techniques compared to traditional data analysis techniques;
  • appreciate the value BI tools and DM for providing knowledge for decision making, in ways unavailable with traditional techniques.

Gained practical skills to:
  • create dimensional models;
  • create DW architectures suitable for different organisations and requirements;
  • interpret results from OLAP and dimensional models;
  • create data analysis models using BI tools;
  • interpret results from BI and DM tools.

Demonstrated the communication skills necessary to:
  • document and communicate DW architectures and BI techniques;
  • work in a team during DW architecture design and BI model development;
  • communicate and coordinate during the team activities.

Graduate Attributes

Monash prepares its graduates to be:
  1. responsible and effective global citizens who:
    1. engage in an internationalised world
    2. exhibit cross-cultural competence
    3. demonstrate ethical values
  2. critical and creative scholars who:
    1. produce innovative solutions to problems
    2. apply research skills to a range of challenges
    3. communicate perceptively and effectively

Assessment Summary

Examination (2 hours): 60%; In-semester assessment: 40%

Assessment Task Value Due Date
Assignment 1 - SQL Server and Data Warehousing 20% Week 7
Assignment 2 - Data Mining 20% Week 12
Examination 1 60% To be advised

Teaching Approach

Lecture and tutorials or problem classes
This teaching and learning approach provides facilitated learning, practical exploration and peer learning.

Feedback

Our feedback to You

Types of feedback you can expect to receive in this unit are:
  • Informal feedback on progress in labs/tutes
  • Graded assignments with comments
  • Solutions to tutes, labs and assignments

Your feedback to Us

Monash is committed to excellence in education and regularly seeks feedback from students, employers and staff. One of the key formal ways students have to provide feedback is through SETU, Student Evaluation of Teacher and Unit. The University's student evaluation policy requires that every unit is evaluated each year. Students are strongly encouraged to complete the surveys. The feedback is anonymous and provides the Faculty with evidence of aspects that students are satisfied and areas for improvement.

For more information on Monash's educational strategy, and on student evaluations, see:
http://www.monash.edu.au/about/monash-directions/directions.html
http://www.policy.monash.edu/policy-bank/academic/education/quality/student-evaluation-policy.html

Previous Student Evaluations of this unit

If you wish to view how previous students rated this unit, please go to
https://emuapps.monash.edu.au/unitevaluations/index.jsp

Unit Schedule

Week Activities Assessment
0   No formal assessment or activities are undertaken in week 0
1 Introduction to Business Intelligence and Data Warehousing  
2 The Dimensional Data Warehouse  
3 Data Cubes and Online Analytical Processing (OLAP) Assignment 1 available to students Week 3
4 Guest Lecture  
5 Applying the Dimensional Model with Microsoft BI Tools  
6 MDX for Complex Analysis  
7 Introduction to Business Data Mining and the Customer Life Cycle Assignment 1 due Week 7
8 Data Mining Techniques 1  
9 Data Mining Techniques 2 Assignment 2 available to students Week 9
10 Data Exploration and Mining with Microsoft Tools  
11 Delivering BI and Performance Management  
12 Revision Assignment 2 due Week 12
  SWOT VAC No formal assessment is undertaken SWOT VAC
  Examination period LINK to Assessment Policy: http://policy.monash.edu.au/policy-bank/
academic/education/assessment/
assessment-in-coursework-policy.html

*Unit Schedule details will be maintained and communicated to you via your MUSO (Blackboard or Moodle) learning system.

Assessment Requirements

Assessment Policy

To pass a unit which includes an examination as part of the assessment a student must obtain:

  • 40% or more in the unit's examination, and
  • 40% or more in the unit's total non-examination assessment, and
  • an overall unit mark of 50% or more.

If a student does not achieve 40% or more in the unit examination or the unit non-examination total assessment, and the total mark for the unit is greater than 50% then a mark of no greater than 49-N will be recorded for the unit

Assessment Tasks

Participation

  • Assessment task 1
    Title:
    Assignment 1 - SQL Server and Data Warehousing
    Description:
    Students will be required to use a given case study to complete the following tasks:

    1) Design and build data cubes based on a given data mart.

    2) Develop OLAP queries.

    3) Carry out OLAP analysis and propose recommendations to address issues identified in the case study.

    This is an individual assignment.
    Weighting:
    20%
    Criteria for assessment:

    Correctness and understanding - as there may be more than one "right" answer in many cases we will look for answers that reflect understanding of the underlying principles and theories.

    Completeness and presentation - that you have answered all parts of each question and presented your answers in a suitably formatted report style.

    Use of evidence and argument - you are able to explain your position by using logical argument drawing on the theory presented in the unit.

    Due date:
    Week 7
  • Assessment task 2
    Title:
    Assignment 2 - Data Mining
    Description:
    Students will be required to use several given data sets (related to customers and their buying behaviour) to complete the following tasks:

    1) Carry out a data mining based exploration of the data sets.

    2) Analyse the findings, and describe and profile the customers and their behaviours.

    3) Recommend strategies for improving business performance, upsell and cross sell, and also target marketing, based on the findings.

    This is an individual assignment.
    Weighting:
    20%
    Criteria for assessment:

    Correctness and understanding - as there may be more than one "right" answer in many cases we will look for answers that reflect understanding of the underlying principles and theories.

    Completeness and presentation - that you have answered all parts of each question and presented your answers in a suitably formatted report style.

    Use of evidence and argument - you are able to explain your position by using logical argument drawing on the theory presented in the unit.

    Due date:
    Week 12

Examinations

  • Examination 1
    Weighting:
    60%
    Length:
    2 hours
    Type (open/closed book):
    Closed book
    Electronic devices allowed in the exam:
    None

Assignment submission

It is a University requirement (http://www.policy.monash.edu/policy-bank/academic/education/conduct/plagiarism-procedures.html) for students to submit an assignment coversheet for each assessment item. Faculty Assignment coversheets can be found at http://www.infotech.monash.edu.au/resources/student/forms/. Please check with your Lecturer on the submission method for your assignment coversheet (e.g. attach a file to the online assignment submission, hand-in a hard copy, or use an online quiz).

Extensions and penalties

Submission must be made by the due date otherwise penalties will be enforced.

You must negotiate any extensions formally with your campus unit leader via the in-semester special consideration process: http://www.infotech.monash.edu.au/resources/student/equity/special-consideration.html.

Returning assignments

Students can expect assignments to be returned within two weeks of the submission date or after receipt, whichever is later

Other Information

Policies

Monash has educational policies, procedures and guidelines, which are designed to ensure that staff and students are aware of the University's academic standards, and to provide advice on how they might uphold them. You can find Monash's Education Policies at:
http://policy.monash.edu.au/policy-bank/academic/education/index.html

Key educational policies include:

Student services

The University provides many different kinds of support services for you. Contact your tutor if you need advice and see the range of services available at www.monash.edu.au/students The Monash University Library provides a range of services and resources that enable you to save time and be more effective in your learning and research. Go to http://www.lib.monash.edu.au or the library tab in my.monash portal for more information. Students who have a disability or medical condition are welcome to contact the Disability Liaison Unit to discuss academic support services. Disability Liaison Officers (DLOs) visit all Victorian campuses on a regular basis

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