Short Title:Business Intelligence
Full Title:Business Intelligence
Module Code:BSIT H4023
 
ECTS credits: 5
NFQ Level:8
Module Delivered in 9 programme(s)
Module Contributor:Brian Watters
Module Description:The purpose of this module is to introduce business and accounting students to the concept of business intelligence and the visualisation of data.
Learning Outcomes:
On successful completion of this module the learner will be able to
  1. Evaluate the key areas contributing to the area of business intelligence
  2. Appraise and assess the technologies used in the area of Business Intelligence
  3. Validate the tools used in the extraction, transformation and loading of data of BI purposes
  4. Analyse existing real world data sets using BI tools
  5. Evaluate BI visualisation tools and techniques
 

Module Content & Assessment

Indicative Content
Overview of business intelligence and analytics
Business Intelligence framework, intelligence creation and usage, BI Governance, BI implementation, BI tools and techniques
Data Warehousing
Definitions and concepts, data warehouse architectures, Data ETL processes, Data warehouse development, implementation, administration and security issues.
Business Performance Management
Definition, planning and monitoring, Key Performance Indicators and metrics, BPM Methodologies, BPM technologies and applications, performance dashboards and scorecards.
Data Mining
concepts and definitions, data mining applications, data mining processes, data mining methods, clustering, classification and association.
Text and Web Mining
concepts and definitions, natural language processing, text mining applications, text mining processes, text mining tools, web mining overview, web content mining and web structure, web usage mining.
Performance Dashboards
Context and definition, types of dashboards, creating effective business metrics, effective dashboard design, visualisation tools and software.
Indicative Assessment Breakdown%
Course Work Assessment %100.00%
Course Work Assessment %
Assessment Type Assessment Description Outcome addressed % of total Assessment Date
Project Use of SAS software to extract, transform, load and process data files. 3,4 40.00 Week 7
Project Use of Tableau Software to extract and present data in graphical format 4,5 30.00 Week 10
Written Report Research project into the collective technologies and techniques used in the area of Business Intelligence. 1 30.00 Sem 1 End
No Final Exam Assessment %
Indicative Reassessment Requirement
Coursework Only
This module is reassessed solely on the basis of re-submitted coursework. There is no repeat written examination.
Reassessment Description
Students are required to submit 3 pieces of work, these are : 1. Written review of BI tools and techniques based on literature research 2. The analysis of a data set using a BI tool 3. The visualisation of a data set using a data visualisation tool

ITB reserves the right to alter the nature and timings of assessment

 

Indicative Module Workload & Resources

Indicative Workload: Full Time
Frequency Indicative Average Weekly Learner Workload
Every Week 2.00
Every Week 2.00
Indicative Workload: Part Time
Frequency Indicative Average Weekly Learner Workload
Every Week 2.00
Every Week 2.00
Resources
Recommended Book Resources
  • Efraim Turban, 2011, Business Intelligence, 2nd Ed., Pearson [ISBN: 9780132478823]
Supplementary Book Resources
  • Robert Spence 2007, Information visualization, Pearson-Prentice Hall Harlow [ISBN: 9780132065504]
  • Wayne W. Eckerson, 2013, Performance Dashboards, Wiley New Jersey [ISBN: 9780470589830]
  • Rajiv Sabherwal, Irma Becerra-Fernandez, 2011, Business Intelligence, Wiley [ISBN: 9780470461709]
  • Michael Towler, Sarah Keast,, Rational Decision Making for Managers [ISBN: 9780470519653]
  • Pang-Ning Tan, Michael Steinbach, Vipin Kumar 2006, Introduction to data mining, Pearson/Addison Wesley Boston, Mass. [ISBN: 9780321420527]
  • Carlo Vercellis 2009, Business intelligence, Wiley [ISBN: 9780470511398]
  • Frank J. Ohlhorst, 2013, Big Data Analytics: Turning Big Data into Big Money, Wiley [ISBN: 9781118147597]
  • Jean-Paul Isson, Jesse Harriott, 2013, Win with Advanced Business Analytics: Creating Business Value from Your Data, Wiley [ISBN: 9781118370605]
This module does not have any article/paper resources
Other Resources

Module Delivered in

Programme Code Programme Semester Delivery
BN_BDMKT_8 Bachelor of Arts (Honours) in Digital Marketing 7 Mandatory
BN_BACFN_8 Bachelor of Business (Honours) in Accounting & Finance [240 ECTS credits] 8 Mandatory
BN_BACFN_B Bachelor of Business (Honours) in Accounting & Finance [Add on 60 ECTS credits] 2 Mandatory
BN_BBSIT_8 Bachelor of Business (Honours) in Information Technology [240 ECTS credits] 8 Mandatory
BN_BBSIT_B Bachelor of Business (Honours) in Information Technology [Add on 60 ECTS credits] 2 Mandatory
BN_BINTL_8 Bachelor of Business (Honours) in International Business [240 ECTS credits] 8 Group Elective 3
BN_BINTL_B Bachelor of Business (Honours) in International Business [Add on 60 ECTS credits] 2 Group Elective 3
BN_BBSST_8 Bachelor of Business (Honours) [240 ECTS credits] 8 Elective
BN_BBSST_B Bachelor of Business (Honours)[Add on 60 ECTS credits] 2 Elective