bus5pb principles of business analytics

PRINCIPLES OF BUSINESS ANALYTICS

BUS5PB

2019

Credit points: 15

Subject outline

This subject introduces you to business and data analytics with a strong focus on practical outcomes that are directly applicable to business contexts. It delivers a comprehensive understanding of current theories, frameworks, applications and technologies that support modern data-driven decision-making process. You will gain hands-on experience in IBM Cognos, SAP Lumira and Microsoft Power BI to design and develop analytics solutions. The subject focuses on key descriptive analytics topics, data wrangling, text processing and data ethics. Industry-based guest lectures will present fresh perspectives on the managerial role in planning and implementing business analytics initiatives and the emerging role of analytics in business performance management. Upon completion, you will be able to transform business problems into analytics solutions, understand key issues,analytics frameworks, techniques, determine business value of analytics outcomes and appreciate its role in BPM.

SchoolLa Trobe Business School

Credit points15

Subject Co-ordinatorKok-Leong Ong

Available to Study Abroad StudentsNo

Subject year levelYear Level 5 - Masters

Exchange StudentsNo

Subject particulars

Subject rules

PrerequisitesN/A

Co-requisitesN/A

Incompatible subjectsN/A

Equivalent subjectsN/A

Special conditionsN/A

Learning resources

Readings

Resource TypeTitleResource RequirementAuthor and YearPublisher
ReadingsData Science for Business: What you need to know about data mining and data analytic thinkingRecommendedProvost and FawcettO'Reilly Media
ReadingsThe Value of Business Analytics: Identifying the Path to ProfitabilityRecommendedStubbsWiley

Graduate capabilities & intended learning outcomes

01. Examine the purpose and importance of analytics within a business environment, alongside implications for technologies, workflows, participation and management.

Activities:
Lectures, Workshops and Assignments1 &2
Related graduate capabilities and elements:
Inquiry and Analytical Skills(Critical Thinking,Creative Problem-solving)
Discipline -Specific Knowledge and Skills(Discipline-Specific Knowledge and Skills)

02. Analyse and evaluate the function of key elements of a typical analytics solution; technology infrastructure, data architecture, data management, analytics methodologies, analytics techniques, reports, dashboards, responsibilities of groups and individuals within the business environment.

Activities:
Lectures, Workshops and Assignment 2
Related graduate capabilities and elements:
Literacies and Communication Skills(Writing)
Inquiry and Analytical Skills(Critical Thinking,Creative Problem-solving)
Discipline -Specific Knowledge and Skills(Discipline-Specific Knowledge and Skills)

03. Evaluate requirements, methodologies and technologies for analytics-based business performance management.

Activities:
Lectures, Workshops and Assignment 3
Related graduate capabilities and elements:
Inquiry and Analytical Skills(Critical Thinking,Creative Problem-solving)
Discipline -Specific Knowledge and Skills(Discipline-Specific Knowledge and Skills)

Subject options

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Start date between: and    Key dates

City Campus, 2019, Semester 1, Night

Overview

Online enrolmentYes

Maximum enrolment size120

Enrolment information Limits of teaching space Order of application

Subject Instance Co-ordinatorKok-Leong Ong

Class requirements

Lecture/WorkshopWeek: 10 - 22
One 3.0 hours lecture/workshop per week on weekdays at night from week 10 to week 22 and delivered via face-to-face.

Assessments

Assessment elementComments%ILO*
Self-service analytics solution development2500 word equivalency4001
Application of analytics design approaches2000 word equivalency3001, 02
Analysis of data-driven decision-making2000 word equivalency3003

City Campus, 2019, Semester 2, Night

Overview

Online enrolmentYes

Maximum enrolment size120

Enrolment information Limits of teaching space Order of application

Subject Instance Co-ordinatorKok-Leong Ong

Class requirements

Lecture/WorkshopWeek: 31 - 43
One 3.0 hours lecture/workshop per week on weekdays at night from week 31 to week 43 and delivered via face-to-face.

Assessments

Assessment elementComments%ILO*
Self-service analytics solution development2500 word equivalency4001
Application of analytics design approaches2000 word equivalency3001, 02
Analysis of data-driven decision-making2000 word equivalency3003