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
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 - 2017
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).
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
Assessment Overview
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.
All University policies are available on the CQUniversity Policy site.
You may wish to view these policies:
- Grades and Results Policy
- Assessment Policy and Procedure (Higher Education Coursework)
- Review of Grade Procedure
- Student Academic Integrity Policy and Procedure
- Monitoring Academic Progress (MAP) Policy and Procedure – Domestic Students
- Monitoring Academic Progress (MAP) Policy and Procedure – International Students
- Student Refund and Credit Balance Policy and Procedure
- Student Feedback – Compliments and Complaints Policy and Procedure
- Information and Communications Technology Acceptable Use Policy and Procedure
This list is not an exhaustive list of all University policies. The full list of University policies are available on the CQUniversity Policy site.
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 Moodle site
This course provides a good knowledge in the area of Big Data and its latest trends and show how the companies are developing their strategies. The assessments included research which has helped students learn about different organization and requirements for Big Data.
More recent trends videos are uploaded on Teaching resources.
Recent research papers and videos were uploaded on Moodle site to help students understand the area of Big Data.
- 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.
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 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
Big Data : Understanding How Data Powers Big Business
Edition: 2013 (2013)
Authors: Schmarzo, Bill
Wiley
Crosspoint Boulevard Crosspoint Boulevard , Crosspoint Boulevard , Indianapolis
ISBN: 978-1-118-73957-0
Binding: Hardcover
Big Data, Big Analytics : Emerging Business Intelligence and Analytic Trends for Today's Businesses
Edition: 2013 (2013)
Authors: Minelli Michael, Dhiraj Ambiga, Chambers Michele
2013 Wiley CIO Series
New Jersey New Jersey , New Jersey , USA
Binding: Paperback
Additional Textbook Information
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
All submissions for this unit must use the referencing style: Harvard (author-date)
For further information, see the Assessment Tasks.
m.jha@cqu.edu.au
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
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
Module/Topic
Business and Organisational Impact of Big Data
Chapter
Chapter 3 and Chapter 4 from Big Data: Understanding How Data Powers Big Business Your Business Degree Schmarzo, Bill 2013 Wiley.
Events and Submissions/Topic
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
Module/Topic
Understanding Decision Theory and Business Analytics
Chapter
Chapter 5 from Big Data: Understanding How Data Powers Big Business Your business degree 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
Module/Topic
Break Week
Chapter
Revise all Chapters and the unit contents covered so far
Events and Submissions/Topic
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
Module/Topic
Creating the Big Data Strategy
Chapter
Chapter 6 from Big Data: Understanding How Data Powers Big Business Your Business Degree Schmarzo, Bill 2013 Wiley.
Events and Submissions/Topic
Module/Topic
Understanding your Value Creation Process
Chapter
Chapter 7 from Big Data: Understanding How Data Powers Big Business Your Business Degree Schmarzo, Bill 2013 Wiley.
Events and Submissions/Topic
Module/Topic
Big Data User Experience Ramifications
Chapter
Chapter 8 from Big Data: Understanding How Data Powers Big Business Your Business Degree 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.
Presentation Due: Week 9 Monday (8 May 2017) 5:00 pm AEST
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 Your Business Degree Schmarzo, Bill 2013 Wiley.
Events and Submissions/Topic
Module/Topic
Solution Engineering
Chapter
Chapter 10 from Big Data: Understanding How Data Powers Big Business Your Business Degree Schmarzo, Bill 2013 Wiley.
Events and Submissions/Topic
Module/Topic
Business Intelligence And Analytics: From Big Data To Big Impact: Self reading and discusion in the class
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
Module/Topic
Review Week
Chapter
Review Week
Events and Submissions/Topic
Module/Topic
No Exam
Chapter
No Exam
Events and Submissions/Topic
Contact information for Dr Meena Jha: Email: m.jha@cqu.edu.au Telephone: ( 02) 9324 5776 Office: Level 6, 400 Kent Street, Sydney Campus. 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. For an individual discussion, please ring during working hours (leave a message if I'm not in and I'll return your call as soon as I can).
1 Written Assessment
You are required to select an (one) application of Big Data in Supply Chain/Logistics, Healthcare, Insurance, Marketing, Finance etc. of your choice. Discuss and compare the key values added by Big Data solutions over traditional methods. You are to write a report on Big Data Technology and services. Your report should address the following in the related context.
• What Big Data is, and the difference between Online and Offline Big Data
• How to select the right Big Data application for your business, project and desired outcomes.
• What are the technologies available in Big Data
• Business Impact of Big Data
• Organisational Impact of Big Data.
The length of the assignment is 2000 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.
The report structure should be clear, easy to read and logical, directly addressing the question. Suitable headers should be used throughout the report. Good use of graphics and charts should be made.
No spelling, punctuation or grammatical errors.
Week 6 Friday (21 Apr 2017) 5:00 pm AEST
Assignment 1 is due on Friday at 17:00 AEST
Week 9 Friday (12 May 2017)
This will be made available to students.
Assessment Marking Criteria: Weighted out of 35%
1. Introduction (7 marks)
2. Difference between online and Offline Data (10 marks)
3. Strategy to select right Big Data application (10 marks)
4. Listed desired outcome from Big Data Solution (10 marks)
5. Discussion on Technologies used in Big data solutions (10 marks)
6. Business impact of Big Data (10 marks)
7. Organisational impact of Big Data (10 marks)
8. Conclusion (10 marks)
9. Quality of Information (10 marks)
10. Grammar Usage (7 marks)
11. References used (6 marks)
- 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.
- Knowledge
- Communication
- Cognitive, technical and creative skills
- Research
- Self-management
- Ethical and Professional Responsibility
2 Presentation
You are required to give a presentation (15 minutes) on how to create a Big Data Strategy and turning the strategy document into action.
You need to select a use case and develop a Big Data Strategy document for the presentation. The presentation will take up one hour of tutorial time from Week 9-Week 12.
You will be informed in week 5 about your presentation schedule. Please check your CQU email.
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.
Week 9 Monday (8 May 2017) 5:00 pm AEST
Certification Date
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)
- 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.
- Knowledge
- Communication
- Cognitive, technical and creative skills
- Research
- Self-management
- Ethical and Professional Responsibility
3 Practical and Written Assessment
You are required to conduct market research and write a report on how Big Data can be used in Decision Support and Business Intelligence (DS&BI). You are required to select/ research a use case for Big Data Strategy. You are required to identify and create business strategy for Big Data use case. 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). Yiu should able to address advanced analytics requirements necessary to support the business strategy they have selected. And 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 followings:
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. Discussion on Data Analytics and MDM to support DS&BI
5. Discuss support of NoSQL for Big Data Analytics.
6. Discussion on 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. Discussion on 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 question. Suitable headers should be used throughout the report. Good use of graphics and charts should be made. No spelling, punctuation or grammatical errors.
Week 12 Friday (2 June 2017) 5:00 pm AEST
Assignment 2 is due on Friday Week 11 at 17:00 AEST.
Exam Week Friday (16 June 2017)
This will be made available to students after the declaration of the term result. Certificate date (required for non exam courses)
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. Discussion on Data Analytics and MDM to support DS&BI. (10 marks)
6. Discuss support of NoSQL for Big Data Analytics. (10 marks)
7. Discussion on 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. Discussion on 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)
- 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.
- Knowledge
- Communication
- Cognitive, technical and creative skills
- Research
- Self-management
- Ethical and Professional Responsibility
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?
