CQUniversity Unit Profile
COIT20253 Business Intelligence using Big Data
Business Intelligence using Big Data
All details in this unit profile for COIT20253 have been officially approved by CQUniversity and represent a learning partnership between the University and you (our student).
The information will not be changed unless absolutely necessary and any change will be clearly indicated by an approved correction included in the profile.
General Information

Overview

Big data management is the organisation, administration and governance of large volumes of both structured and unstructured data. In this unit we explore big data within the context of business intelligence. Students learn general big data structure, concepts of business intelligence, alignment of big data to business intelligence and how big data can be used in the organisational business intelligence. Students learn how big data is changing businesses and how organisations can take an advantage of big data in the decision making. In today’s world organisations are making decisions on non-traditional, unstructured data. Students learn how organisations are including non-traditional unstructured valuable data with the traditional enterprise data to do the business intelligence analysis. Note: If you have completed unit COIT20236 then you cannot take this unit.

Details

Career Level: Postgraduate
Unit Level: Level 9
Credit Points: 6
Student Contribution Band: 8
Fraction of Full-Time Student Load: 0.125

Pre-requisites or Co-requisites

Prerequisites: COIT20250 e-Business Systems, COIT20245 Introduction to Programming and COIT20247 Database Design and Development

Important note: Students enrolled in a subsequent unit who failed their pre-requisite unit, should drop the subsequent unit before the census date or within 10 working days of Fail grade notification. Students who do not drop the unit in this timeframe cannot later drop the unit without academic and financial liability. See details in the Assessment Policy and Procedure (Higher Education Coursework).

Offerings For Term 1 - 2018

Brisbane
Distance
Melbourne
Rockhampton
Sydney

Attendance Requirements

All on-campus students are expected to attend scheduled classes – in some units, these classes are identified as a mandatory (pass/fail) component and attendance is compulsory. International students, on a student visa, must maintain a full time study load and meet both attendance and academic progress requirements in each study period (satisfactory attendance for International students is defined as maintaining at least an 80% attendance record).

Class and Assessment Overview

Recommended Student Time Commitment

Each 6-credit Postgraduate unit at CQUniversity requires an overall time commitment of an average of 12.5 hours of study per week, making a total of 150 hours for the unit.

Class Timetable

Bundaberg, Cairns, Emerald, Gladstone, Mackay, Rockhampton, Townsville
Adelaide, Brisbane, Melbourne, Perth, Sydney

Assessment Overview

1. Written Assessment
Weighting: 35%
2. Presentation
Weighting: 25%
3. Practical and Written Assessment
Weighting: 40%

Assessment Grading

This is a graded unit: your overall grade will be calculated from the marks or grades for each assessment task, based on the relative weightings shown in the table above. You must obtain an overall mark for the unit of at least 50%, or an overall grade of ‘pass’ in order to pass the unit. If any ‘pass/fail’ tasks are shown in the table above they must also be completed successfully (‘pass’ grade). You must also meet any minimum mark requirements specified for a particular assessment task, as detailed in the ‘assessment task’ section (note that in some instances, the minimum mark for a task may be greater than 50%). Consult the University’s Grades and Results Policy for more details of interim results and final grades.

Previous Student Feedback

Feedback, Recommendations and Responses

Every unit is reviewed for enhancement each year. At the most recent review, the following staff and student feedback items were identified and recommendations were made.

Feedback from Through Moodle site

Feedback

Interesting unit, very practical, excellent, topics are good and materials provided are nice

Recommendation

Continue providing current research study materials

Feedback from Through Moodle site

Feedback

Slides should be more informative

Recommendation

Continue enhancing lecture slides and assessments

Unit Learning Outcomes
On successful completion of this unit, you will be able to:
  1. Identify and describe the principles and concepts of big data.
  2. Evaluate and explain how large volume of structured and unstructured data are managed in an organization.
  3. Examine how big data can be aligned to business intelligence for decision making.
  4. Assess how organizations are including non-traditional valuable data with the traditional enterprise data to do the business intelligence analysis.
  5. Evaluate and report the role of Knowledge Management Systems to support knowledge creation, gathering and sharing.
  6. Effectively communicate business information needs and construct professional reports.

Australian Computer Society (ACS) recognises the Skills Framework for the Information Age (SFIA). SFIA is in use in over 100 countries and provides a widely used and consistent definition of ICT skills. SFIA is increasingly being used when developing job descriptions and role profiles.

ACS members can use the tool MySFIA to build a skills profile at https://www.acs.org.au/professionalrecognition/mysfia-b2c.html

This unit contributes to the following workplace skills as defined by SFIA. The SFIA code is included:

  • Information Management (IRMG)
  • Information Analysis (INAN)
  • Emerging Technology Monitoring (EMRG)
  • Database/Respository Design (DBDS)
  • Solution Architecture (ARCH)

Alignment of Learning Outcomes, Assessment and Graduate Attributes
N/A Level
Introductory Level
Intermediate Level
Graduate Level
Professional Level
Advanced Level

Alignment of Assessment Tasks to Learning Outcomes

Assessment Tasks Learning Outcomes
1 2 3 4 5 6
1 - Written Assessment - 35%
2 - Presentation - 25%
3 - Practical and Written Assessment - 40%

Alignment of Graduate Attributes to Learning Outcomes

Graduate Attributes Learning Outcomes
1 2 3 4 5 6
1 - Knowledge
2 - Communication
3 - Cognitive, technical and creative skills
4 - Research
5 - Self-management
6 - Ethical and Professional Responsibility
7 - Leadership
8 - Aboriginal and Torres Strait Islander Cultures

Alignment of Assessment Tasks to Graduate Attributes

Assessment Tasks Graduate Attributes
1 2 3 4 5 6 7 8
1 - Written Assessment - 35%
2 - Presentation - 25%
3 - Practical and Written Assessment - 40%
Textbooks and Resources

Textbooks

Prescribed

Big Data: Understanding How Data Powers Big Business

(2013)
Authors: Schmarzo, Bill
Wiley
Crosspoint Boulevard, Indianapolis Crosspoint Boulevard, Indianapolis , USA
ISBN: 978-1-118-73957-0
Binding: Other
Supplementary

Big Data, Big Analytics: Emerging Business Intelligence and Analytic Trends for Today's Businesses

(2013)
Authors: Minelli Michael, Dhiraj Ambiga, Chambers Michele
Wiley CIO Series
Hoboken Hoboken , New Jersey , USA
ISBN: 978-1-118-14760-3
Binding: Other

Additional Textbook Information


IT Resources

You will need access to the following IT resources:
  • CQUniversity Student Email
  • Internet
  • Unit Website (Moodle)
  • Hadoop (requires 8 GB RAM)
  • MS Excel Solver Add-in (MS office) Power Query is required to be added on EXCEL 2013. It is a patch which needs to be downloaded and appears on Option-->Add-in. It requires IE 9 or later in the Computer labs.
  • MS Office
  • ODBC driver for sandbox (Students should able to configure it)
  • Oracle VM Virtual Box
  • Power View feature in Microsoft Excel 2013.
  • QlikView http://www.qlik.com/us/explore/products/free-download
  • SandBox 2.4
  • talend Platform for Big Data integration (30 days trial is free) http://www.talend.com/products/big-data
Referencing Style

All submissions for this unit must use the referencing style: Harvard (author-date)

For further information, see the Assessment Tasks.

Teaching Contacts
Meena Jha Unit Coordinator
m.jha@cqu.edu.au
Schedule
Week 1 Begin Date: 05 Mar 2018

Module/Topic

Introduction to Big Data. What is Big Data and Why Is It Important? How Big Data will change Your Job, Your Company and Your Industry

Chapter

CRO And Chapter 1 from Big Data, Big Analytics : Emerging Business Intelligence and Analytic Trends for Today's Businesses, Minelli Michael, Dhiraj Ambiga, Chambers Michele, 2013 Wiley & Sons

Events and Submissions/Topic

Week 2 Begin Date: 12 Mar 2018

Module/Topic

Big Data Technology

Chapter

Chapter 3 from Big Data, Big Analytics : Emerging Business Intelligence and Analytic Trends for Today's Businesses, Minelli Michael, Dhiraj Ambiga, Chambers Michele, 2013 Wiley & Sons

Events and Submissions/Topic

Week 3 Begin Date: 19 Mar 2018

Module/Topic

Business and Organisational Impact of Big Data

Chapter

Chapter 3 and Chapter 4 from Big Data: Understanding How Data Powers Big Business  Schmarzo, Bill 2013 Wiley.

Events and Submissions/Topic

Week 4 Begin Date: 26 Mar 2018

Module/Topic

Big Data Architecture and Patterns

Chapter

CRO Provided 1. Oracle Information Architecture: An Architect’s Guide to Big Data 2. Big Data Architecture and Patterns, Part 1 Introduction to Big Data Classification and Architecture.

Events and Submissions/Topic

Week 5 Begin Date: 02 Apr 2018

Module/Topic

Understanding Decision Theory and Business Analytics

Chapter

Chapter 5 from Big Data: Understanding How Data Powers Big Business  Schmarzo, Bill 2013 Wiley. Chapter 5 from Big Data, Big Analytics : Emerging Business Intelligence and Analytic Trends for Today's Businesses, Minelli Michael, Dhiraj Ambiga, Chambers Michele, 2013 Wiley & Sons

Events and Submissions/Topic

Vacation Week Begin Date: 09 Apr 2018

Module/Topic

Break Week

Chapter

Revise all Chapters and the unit contents covered so far

Events and Submissions/Topic

Week 6 Begin Date: 16 Apr 2018

Module/Topic

Information and Data Management

Chapter

Chapter 4 from Big Data, Big Analytics : Emerging Business Intelligence and Analytic Trends for Today's Businesses, Minelli Michael, Dhiraj Ambiga, Chambers Michele, 2013 Wiley & Sons

Events and Submissions/Topic

Assignment 1 Due: Week 6 Monday (16 Apr 2018) 11:45 pm AEST
Week 7 Begin Date: 23 Apr 2018

Module/Topic

Creating the Big Data Strategy.

Chapter

Chapter 6 from Big Data: Understanding How Data Powers Big Business Schmarzo, Bill 2013 Wiley.


Events and Submissions/Topic

Week 8 Begin Date: 30 Apr 2018

Module/Topic

Understanding the Value Creation Process.

Chapter

Chapter 7 from Big Data: Understanding How Data Powers Big Business Schmarzo, Bill 2013 Wiley.

Events and Submissions/Topic

Week 9 Begin Date: 07 May 2018

Module/Topic

Big Data User Experience Ramifications

Chapter

Chapter 8 from Big Data: Understanding How Data Powers Big Business  Schmarzo, Bill 2013 Wiley.

Events and Submissions/Topic

The presentation will take up one hour of tutorial time from Week 9-Week 12. Students will be informed in week 5 about their presentation schedule. It is very important for all students to meet the due date of their respective presentation.


Assignment 2: Presentation Due: Week 9 Monday (7 May 2018) 11:45 pm AEST
Week 10 Begin Date: 14 May 2018

Module/Topic

Operational Intelligence Real Time Business Analytics from Big Data Use Cases for Operational Intelligence

Identifying Big Data Use Cases

Chapter

CRO and Chapter 9 from Big Data: Understanding How Data Powers Big Business Schmarzo, Bill 2013 Wiley.

Events and Submissions/Topic

Week 11 Begin Date: 21 May 2018

Module/Topic

Solution Engineering

Chapter

Chapter 10 from Big Data: Understanding How Data Powers Big Business  Schmarzo, Bill 2013 Wiley.

Events and Submissions/Topic

Week 12 Begin Date: 28 May 2018

Module/Topic

Business Intelligence And Analytics: From Big Data To Big Impact

Chapter

CRO.MIS Quarterly Business Intelligence and Analytics: From Big Data to Big Impact, Hsinchun Chen, Roger H.L.Chiang, and Veda C. Storey Vol. 36 No. 4 pp1165-1188 December 2012 Self-reading and discussion in the class.

Events and Submissions/Topic

Assignment 3: Practical and Written Assessment: Creating a Big Data Strategy Due: Week 12 Monday (28 May 2018) 11:45 pm AEST
Review/Exam Week Begin Date: 04 Jun 2018

Module/Topic

Review Week

Chapter

Review Week

Events and Submissions/Topic

Exam Week Begin Date: 11 Jun 2018

Module/Topic

No Exam

Chapter

No Exam

Events and Submissions/Topic

Term Specific Information

Contact information for Dr Meena Jha: Email: m.jha@cqu.edu.au Office: Level 6, 400 Kent Street, Sydney Campus; P +61 2 9324 5776 | X 55776. Please submit questions about the course through the 'Q&A' discussion forum in Moodle - that way, everyone can benefit from the questions and answers. If you have any individual queries, please email me and I'll try to get back to you within a day or so.

Assessment Tasks

1 Written Assessment

Assessment Title
Assignment 1

Task Description

The ability of Business Intelligence (BI) technologies to provide historical, current, and predictive views of business operations based on the collection, extraction, and analysis of business data to improve decision has been the basis of several studies. More recently, “Big Data” and “Big Data Analytics” have further stirred the interest of researchers and practitioners alike. You have been requested to prepare a report focusing on one of the following topics:

1. Big Data for Supply Chain and Operations Management

2. Sports Analytics

3. Agricultural Analytics

4. Fraud Detection in Banking Sector

5. Big Data for Sentiment Analysis

The report should be well researched and written in accordance with Harvard referencing style.The assignment will be marked out of a total of 100 marks and forms 35% of the total assessment for the unit. ALL assignments will be checked for plagiarism by Turnitin. You have been requested to prepare a report. Your target audience is business executives, who have extensive business experience but limited ICT knowledge. They would like to be informed as to how new Big Data technologies may be beneficial for their business. Please note that standard report structure, including an executive summary, must be adhered to.

The main body of the report should include the following topics.

1. Data Collection and Storage

  • Data collection system (what kind of data should be collected and how)
  • Storage system (what are the requirements of the storage and how to achieve them)

2. Data in Action

  • Consumer-centric product design (what is it and how to do it)
  • Recommendation system (what is it and how to do it)

3. Business continuity

  • How online business can survive in case of power outage or other disasters?

The length of the assignment is 3000 words. You are required to do extensive reading of more than 10 appropriate and relevant chosen topics in Big Data application Please do in-text referencing of all chosen readings. Newspaper and magazine reports should be limited to a maximum of 2. A comprehensive report covering all key aspects of the topic selected is required. Report should be extremely well supported with relevant case studies. Any assumptions made are clearly noted. DO NOT use Wikipedia as a reference. The use of unqualified references will result in the deduction of marks.

The report structure should be clear, easy to read and logical, directly addressing the questions. Suitable headers should be used throughout the report. Good use of graphics and charts should be made.

No spelling, punctuation or grammatical errors.


Assessment Due Date

Week 6 Monday (16 Apr 2018) 11:45 pm AEST

Assignment 1 is due on Monday Week 6 at 11:45PM


Return Date to Students

Week 8 Monday (30 Apr 2018)

This will be made available to students.


Weighting
35%

Assessment Criteria

Assessment Marking Criteria: Weighted out of 35%

Report formatting (font, header and footer, table of content, numbering, referencing) 5 Marks

Professional communication (correct spelling, grammar, formal business language used) 5 Marks

Executive summary 10 Marks

Report introduction 10 Marks

Data Collection and Storage 20 Marks

Data in Action 30 Marks

Business continuity 10 Marks

Conclusion and Recommendations 10 Marks

Total = 100.00


Referencing Style

Submission
Online

Submission Instructions
This is an individual assignment. Please upload your file on Moodle platform.

Learning Outcomes Assessed
  • Identify and describe the principles and concepts of big data.
  • Evaluate and explain how large volume of structured and unstructured data are managed in an organization.
  • Examine how big data can be aligned to business intelligence for decision making.
  • Assess how organizations are including non-traditional valuable data with the traditional enterprise data to do the business intelligence analysis.
  • Evaluate and report the role of Knowledge Management Systems to support knowledge creation, gathering and sharing.
  • Effectively communicate business information needs and construct professional reports.


Graduate Attributes
  • Knowledge
  • Communication
  • Cognitive, technical and creative skills
  • Research
  • Self-management
  • Ethical and Professional Responsibility

2 Presentation

Assessment Title
Assignment 2: Presentation

Task Description

The assignment will be marked out of a total of 25 marks and forms 25% of the total assessment for the unit.This presentation is based on your Assignment 3. Your will propose a research study that will involve investigating and determining how a particular large organisation use Big Data for developing Big Data Strategy and driving productivity, in a no more than 5-minute presentation in class for feedback and approval by the lecturer/ Tutor in week 7. The presentation of your findings in this project would be of about 15-minute duration which will start from week 9.

Choose any one of the following topic for presentation.

1. Big data and new decision-making techniques/models/approaches;

2. Organisational and cultural issues of the ‘Data-driven’ organisation;

3. Leveraging big Data for enhancing decision making and creating new business models

4. Social networks for exploiting knowledge or creating intelligence;

You are required to give a presentation on how to create a Big Data Strategy and turning the strategy document into action. It is very important for all students to meet the due date of their respective presentation. Presentation will be assessed during the presentation time. You should focus on how to create a Big Data Strategy and turning the strategy document into action and the required Big Data technology.


Assessment Due Date

Week 9 Monday (7 May 2018) 11:45 pm AEST


Return Date to Students

Week 11 Monday (21 May 2018)

Certification Date


Weighting
25%

Assessment Criteria

Marking criteria for evaluating the contact of the Presentation:weighted 25%

1. Subject Knowledge (5 marks)

2. Explanations from evidence (5 marks)

3. Graphics, figures, tables included (5 marks)

4. Conclusions (5 marks)

5. Questions (5 marks)


Referencing Style

Submission
Online

Submission Instructions
Submit your presentation in MS word please. No ppt slides for Moodle submission.

Learning Outcomes Assessed
  • Identify and describe the principles and concepts of big data.
  • Evaluate and explain how large volume of structured and unstructured data are managed in an organization.
  • Examine how big data can be aligned to business intelligence for decision making.
  • Assess how organizations are including non-traditional valuable data with the traditional enterprise data to do the business intelligence analysis.
  • Evaluate and report the role of Knowledge Management Systems to support knowledge creation, gathering and sharing.
  • Effectively communicate business information needs and construct professional reports.


Graduate Attributes
  • Knowledge
  • Communication
  • Cognitive, technical and creative skills
  • Research
  • Self-management
  • Ethical and Professional Responsibility

3 Practical and Written Assessment

Assessment Title
Assignment 3: Practical and Written Assessment: Creating a Big Data Strategy

Task Description

The assignment will be marked out of a total of 100 marks and forms 40% of the total assessment for the unit.In recent years, the ability of Business Intelligence (BI) technologies to provide historical, current, and predictive views of business operations based on the collection, extraction, and analysis of business data to improve decision has been the basis of several studies.

In this assignment you are required to write a research report focusing on one of the following topics (which you have already chosen for presentation and have discussed with your tutor)

1. Big data and new decision-making techniques/models/approaches;

2. Organisational and cultural issues of the ‘Data-driven’ organisation;

3. Leveraging big Data for enhancing decision making and creating new business models

4. Social networks for exploiting knowledge or creating intelligence;

The report should be well researched. Business strategy should be mapped clearly to business initiatives, objectives and tasks. You should able to define required technology stack and required data and analytics architecture for Big data for DS&BI including the Master Data Management (MDM).You should able to address advanced analytics requirements necessary to support the business strategy selected and outline the role social media plays in organisations decision making process. You are required to discuss Big Data Value creation process. The report should address the following:

1. Identify, create and discuss Business Strategy for a Big Data use case

2. Identify and align business initiatives, objectives and tasks with the developed Business Strategy.

3. Identify and discuss the required Technology Stack

4. Discuss Data Analytics and MDM to support DS&BI

5. Discuss support of NoSQL for Big Data Analytics.

6. Discuss different NoSQL Databases and its use in Big Data use case you have chosen.

7. Role of Social media in organisation's decision making process

8. Discuss Big Data Value creation process.

The length of the assignment is 3000 words. You are required to do extensive reading of more than 10 appropriate and relevant chosen topics in Big Data use case. Please do in-text referencing of all chosen readings. Newspaper and magazine reports should be limited to a maximum of 2. A comprehensive report covering all key aspects of the topic selected is required. Report should be extremely well supported with relevant case studies. Any assumptions made are clearly noted. The report structure should be clear, easy to read and logical, directly addressing the questions. Suitable headers should be used throughout the report. Good use of graphics and charts should be made. No spelling, punctuation or grammatical errors.


Assessment Due Date

Week 12 Monday (28 May 2018) 11:45 pm AEST


Return Date to Students

This will be made available to students after the declaration of the term result on Certification of Grades date.


Weighting
40%

Assessment Criteria

Marking Criteria: Weighted out of 40%

1. Introduction (5 marks)

2. Identify, create and discuss Business strategy for a Big Data use case. (10 marks)

3. Identify and align business initiatives, objectives and Tasks with the developed Business Strategy. (10 marks)

4. Identify and discuss the required Technology Stack. (10 marks)

5. Discuss Data Analytics and MDM to support DS&BI. (10 marks)

6. Discuss support of NoSQL for Big Data Analytics. (10 marks)

7. Discuss different NoSQL Databases and its use in Big Data use case you have chosen.(10 marks)

8. Role of Social media and human elements in organisations decision making process.(10 marks)

9. Discuss Big Data Value creation process.(5 marks)

10. Conclusion (5 marks)

11. Quality of Information (5 marks)

12. Grammar Usage (5 marks)

3. References used (5 marks)


Referencing Style

Submission
Online

Submission Instructions
This is an individual assessment. Please submit your report on Moodle.

Learning Outcomes Assessed
  • Identify and describe the principles and concepts of big data.
  • Evaluate and explain how large volume of structured and unstructured data are managed in an organization.
  • Examine how big data can be aligned to business intelligence for decision making.
  • Assess how organizations are including non-traditional valuable data with the traditional enterprise data to do the business intelligence analysis.
  • Evaluate and report the role of Knowledge Management Systems to support knowledge creation, gathering and sharing.
  • Effectively communicate business information needs and construct professional reports.


Graduate Attributes
  • Knowledge
  • Communication
  • Cognitive, technical and creative skills
  • Research
  • Self-management
  • Ethical and Professional Responsibility

Academic Integrity Statement

As a CQUniversity student you are expected to act honestly in all aspects of your academic work.

Any assessable work undertaken or submitted for review or assessment must be your own work. Assessable work is any type of work you do to meet the assessment requirements in the unit, including draft work submitted for review and feedback and final work to be assessed.

When you use the ideas, words or data of others in your assessment, you must thoroughly and clearly acknowledge the source of this information by using the correct referencing style for your unit. Using others’ work without proper acknowledgement may be considered a form of intellectual dishonesty.

Participating honestly, respectfully, responsibly, and fairly in your university study ensures the CQUniversity qualification you earn will be valued as a true indication of your individual academic achievement and will continue to receive the respect and recognition it deserves.

As a student, you are responsible for reading and following CQUniversity’s policies, including the Student Academic Integrity Policy and Procedure. This policy sets out CQUniversity’s expectations of you to act with integrity, examples of academic integrity breaches to avoid, the processes used to address alleged breaches of academic integrity, and potential penalties.

What is a breach of academic integrity?

A breach of academic integrity includes but is not limited to plagiarism, self-plagiarism, collusion, cheating, contract cheating, and academic misconduct. The Student Academic Integrity Policy and Procedure defines what these terms mean and gives examples.

Why is academic integrity important?

A breach of academic integrity may result in one or more penalties, including suspension or even expulsion from the University. It can also have negative implications for student visas and future enrolment at CQUniversity or elsewhere. Students who engage in contract cheating also risk being blackmailed by contract cheating services.

Where can I get assistance?

For academic advice and guidance, the Academic Learning Centre (ALC) can support you in becoming confident in completing assessments with integrity and of high standard.

What can you do to act with integrity?