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CIS8008 Business Intelligence

Semester 1, 2021 On-campus Toowoomba
Short Description: Business Intelligence
Units : 1
Faculty or Section : Faculty of Business, Education, Law and Arts
School or Department : School of Business
Student contribution band : Band 2
ASCED code : 020307 - Decision Support Systems
Grading basis : Graded
Version produced : 11 April 2021


Examiner: Michael Lane

Other requisites

Students are required to have access to a personal computer, e-mail capabilities and Internet access to UConnect. Current details of computer requirements can be found at


It is important for all professions to have a broad comprehension of business intelligence in terms of current and emerging technology trends and how business intelligence can be applied to support data-driven decision-making. They need to have a broad knowledge of business intelligence, underlying data warehouse and big data architecture to be able apply data mining and data visualisation to support decision-making of organisations in order to achieve superior business performance management. Business intelligence plays a critical role in ensuring that organisations achieve strategic goals by monitoring organisational performance and achievement of day-to-day operational goals.


This course provides students with a broad investigation of theory, design, implementation and application of business intelligence systems in an organisational context of evidence based decision making for enhanced business performance. Students will analyse and apply data driven decision making, data warehouse, big data architecture and business intelligence tools to support improved decision making in organisations. Students will be assessed on their knowledge and comprehension of the design implementation and use of business intelligence systems and application of data mining and data visualisation tools to help solve real world business problems. The architecture, implementation, and practical use of business intelligence are considered in current and real life contexts.


On successful completion of this course, students should be able to:

  1. critically analyse, design and recommend how data management systems (data warehousing and data lakes) can be implemented using different approaches and technologies to support business intelligence;
  2. analyse and apply strategies processes and underlying technologies for effective management of data to make evidence based decisions;
  3. critically analyse organisational and societal problems using descriptive and predictive analysis and internal and external data sources to generate insight, create value and support evidence based decision making;
  4. examine legal, ethical and privacy dilemmas that arise from the use if business intelligence, analytics and evidence based decisions making to comply with legal and regulatory requirements;
  5. communicate effectively in a clear and concise manner in written report style for both senior and middle management with correct and appropriate acknowledgment of the main ideas presented and discussed.


Description Weighting(%)
1. Decision making and business intelligence 10.00
2. Business intelligence systems components and tools 10.00
3. Data warehousing and big data architecture 10.00
4. Data mining 30.00
5. Data visualisation 10.00
6. Business performance management 20.00
7. Business intelligence implementation/utilisation challenges and opportunities 10.00

Text and materials required to be purchased or accessed

ALL textbooks and materials available to be purchased can be sourced from USQ's Online Bookshop (unless otherwise stated). (

Please contact us for alternative purchase options from USQ Bookshop. (

Sharda, R, Delen, D & Turban, E 2017, Business intelligence: analytics, and data science: a managerial perspective, 4th global edn, Pearson, Harlow, Essex.

Reference materials

Reference materials are materials that, if accessed by students, may improve their knowledge and understanding of the material in the course and enrich their learning experience.
Jones, B 2014, Communicating data with tableau: designing, developing and delivering data visualizations, O'Reilly, Sebastopol, California.
(available as Kindle or in hard copy.)
Kimball, R & Ross, M 2013, The data warehouse toolkit: the complete guide to dimensional modeling, 3rd edn, John Wiley & Sons, New York.
(available to view online via USQ Library - note there are some restrictions on usage, such as no printing or limited printing of e-books.)
North, M 2012, Data mining for the masses, The Global Textbook Project.
(available at:

Student workload expectations

Activity Hours
Directed Study 36.00
Independent Study 129.00

Assessment details

Description Marks out of Wtg (%) Due Date Objectives Assessed Notes
ASST 1 - WRITTEN REPORT 100 20 19 Mar 2021 1,5
ASST 2 - WRITTEN PRAC REPORT 100 30 23 Apr 2021 2,3,5
ASST 3 - WRITTEN PRAC REPORT 100 50 24 May 2021 3,4,5

Important assessment information

  1. Attendance requirements:
    Online: If you are an international student in Australia, you are advised to attend all classes at your campus. For all other students, there are no attendance requirements for this course. However, it is the students' responsibility to study all material provided to them or required to be accessed by them to maximise their chance of meeting the objectives of the course and to be informed of course-related activities and administration.

    On-campus: It is the students' responsibility to attend and participate appropriately in all activities (such as lectures, tutorials, laboratories and practical work) scheduled for them, and to study all material provided to them or required to be accessed by them to maximise their chance of meeting the objectives of the course and to be informed of course-related activities and administration.

  2. Requirements for students to complete each assessment item satisfactorily:
    To satisfactorily complete an individual assessment item a student must achieve at least 50% of the marks. (Depending upon the requirements in Statement 4 below, students may not have to satisfactorily complete each assessment item to receive a passing grade in this course.)

  3. Penalties for late submission of required work:
    Students should refer to the Assessment Procedure (point 4.2.4)

  4. Requirements for student to be awarded a passing grade in the course:
    To be assured of receiving a passing grade a student must achieve at least 50% of the total weighted marks available for the course.

  5. Method used to combine assessment results to attain final grade:
    The final grades for students will be assigned on the basis of the aggregate of the weighted marks obtained for each of the summative assessment items in the course.

  6. Examination information:
    Due to COVID-19 the requirements for S1 2021 are: There is no examination in this course.

    Requirements after S1, 2021:
    This is a restricted examination. The only materials that candidates may use in the examination for this course are:
    1. writing materials. These must be non-electronic and free from material which could give the student an unfair advantage in the examination.
    2. an unmarked non-electronic translation dictionary (but not technical dictionary). A student whose first language is not English may take a translation dictionary into the examination room. A translation dictionary with any handwritten notes will not be permitted. Translation dictionaries will be subject to perusal and may be removed from the candidate's possession until appropriate disciplinary action is completed if found to contain material that could give the candidate an unfair advantage.
    3. a calculator which cannot hold textual information (students must indicate on their examination paper the make and model of any calculator(s) they use during the examination).

  7. Examination period when Deferred/Supplementary examinations will be held:
    Not applicable.

  8. University Student Policies:
    Students should read the USQ policies: Definitions, Assessment and Student Academic Misconduct to avoid actions which might contravene University policies and practices. These policies can be found at

Assessment notes

  1. Referencing in assignments:
    Harvard (AGPS) is the referencing system required in this course. Students should use Harvard (AGPS) style in their assignments to format details of the information sources they have cited in their work. The Harvard (AGPS) style to be used is defined by the USQ Library's referencing guide at

Date printed 11 April 2021