



Study with the several resources on Docsity
Earn points by helping other students or get them with a premium plan
Prepare for your exams
Study with the several resources on Docsity
Earn points to download
Earn points by helping other students or get them with a premium plan
Main points of this exam paper are: Business Intelligence, Historical Progression, Data Warehouse, Developing One, Visualisation Techniques, Anomaly Detection, Mining Techniques, Typical Architecture, Warehousing Tools, Data Mart
Typology: Exams
1 / 5
This page cannot be seen from the preview
Don't miss anything!




Semester 1 Examinations 2012/
Module Code: COMP
School: Science and Informatics
Programme Title: Bachelor of Science (Honours) in Cloud Computing, Higher Diploma in Sceince in Cloud Computing, Higher Diploma in Sceince in Cloud & Mobile Software Development.
Programme Code: KCLDC_8_Y KCMSD_8_Y KCLCO_8_Y
External Examiner(s): Dr David White Internal Examiner(s): Mr Karl O’Connell, Mr Aengus Daly
Instructions: Answer question one and any two other questions
Duration: 2 hours
Sitting: Winter 2012
Requirements for this examination:
Note to Candidates: Please check the Programme Title and the Module Title to ensure that you are attempting the correct examination. If in doubt please contact an Invigilator.
Q.1 Compulsory Question - Total 40 Marks – Answer any 4 parts.
a) Explain what is meant by CRISP-DM. Detail 2 of the steps involved.
10 Marks
b) Write a brief note explaining what Business Intelligence is. You may give its historical progression and some of its various categories.
10 Marks
c) Briefly explain what a Data Warehouse is, outlining some of the key steps involved in developing one.
10 Marks
d) Why are visualisation techniques important in Business Intelligence? Outline some techniques and some technologies used in this area.
10 Marks
e) Explain what anomaly detection is, giving some of its uses and some of the data mining techniques involved. 10 Marks
[Total 40 Marks]
Q.4 Data Mining and Data Quality – Total 30 Marks
a) Explain the term data mining. 4 Marks
b) In relation to data mining, the 4 main operations are: Predictive Modeling, Database Segmentation, Link Analysis & Deviation Detection. Discuss any 2 in detail.
12 Marks
c) List and explain the important characteristics of data mining tools. 8 Marks
d) Discuss how data integration is important for ensuring data quality and explain two of the techniques for achieving data integration.
6 Marks
Q.5 Applied Business Intelligence – Total 30 Marks
David is the IT Manager of a medium sized car rental company, CarDeal. With a staff of 360, a fleet of 500 vehicles and 5 nationwide branches; the company is looking to expand. CarDeal has 2 commercial relational database systems and a separate finance IT system. CarDeal have a history of bringing in outside consultants for large IT projects. David has asked you for advice on Data Warehousing (DW) and OLAP. You may make any reasonable assumptions to compliment your answer as well as giving details of appropriate technologies.
a) Explain to David what^ the key benefits^ are^ of implementing a DW and OLAP system in relation to Business Performance Management.
10 Marks
b) Explain what is meant by ELT and why it is important. 10 Marks
c) What would you envisage to be the main challenges to implementing a Data Warehouse in CarDeal and how these may be overcome?
10 Marks
[Total 30 Marks]
Q.6 Applied Business Intelligence – Total 30 Marks
Jennifer is the CEO of a small airline company, AIRO, which has a fleet of 50 planes and a staff of 260. The company has been in operation for 16 years.
Jennifer is interested in strengthening her business using data analytics. She studied mathematics in college, some 18 years ago and would like to be given some mathematical/statistical information where relevant. She would also welcome some technology advice where relevant. Currently AIRO has are two separate IT systems.
You may make any assumptions that are reasonable.
a) Jennifer is interested in the area of prediction and forecasting^ of her airline customer numbers, outline a data analytics technique in this area and how it would benefit her business.
15 Marks
b) Jennifer would^ like a way of finding her best profit generating customers and offering them incentives etc to strengthen their loyalty to the company. Using a data mining technique such as Decision Trees (or any other), briefly explain to Jennifer how it works, how it could be used to address her needs and any other business ideas which would help her here.
15 Marks
[Total 30 Marks]