DATA-DRIVEN BUSINESS ANALYSIS
BUA5BAM
2020
Credit points: 15
Subject outline
The modern approach to organisational decision-making is increasingly data driven. You will learn the role of data as the means to developing strategies within organisations as one of the ways to drive innovation and decision-making. You will become familiar with the different types of data that can be analysed to influence managerial decision-making across a range of business problems. Various recent application example of using data to drive business initiatives, such as change, customer engagement and marketing will also be introduced. You will undertake hands-on data analysis using familiar tools like Excel, and learn first-hand the techniques of data storytelling and visualisation to achieve business outcomes. Finally, other important considerations, such as governance and ethics around data and its use in business, will also be covered in this subject.
School: La Trobe Business School (Pre 2022)
Credit points: 15
Subject Co-ordinator: Ged Kennett
Available to Study Abroad/Exchange Students: Yes
Subject year level: Year Level 5 - Masters
Available as Elective: No
Learning Activities: N/A
Capstone subject: No
Subject particulars
Subject rules
Prerequisites: Students must be enrolled in LMMBA or HZMBHA or LMMBAH or LMMBAA or LZFABA or LMPAB or LMAFMB or LMPMB to do this subject
Co-requisites: N/A
Incompatible subjects: BUO5BAM
Equivalent subjects: BUO5BAM
Quota Management Strategy: N/A
Quota-conditions or rules: N/A
Special conditions: N/A
Minimum credit point requirement: N/A
Assumed knowledge: N/A
Learning resources
Big Data MBA: Driving Business Strategies with Data Science
Resource Type: Book
Resource Requirement: Recommended
Author: Bill Schmarzo
Year: N/A
Edition/Volume: 1st Edition
Publisher: Kindle Edition, Wiley
ISBN: N/A
Chapter/article title: N/A
Chapter/issue: N/A
URL: N/A
Other description: N/A
Source location: N/A
Storytelling with Data: A Data Visualisation Guide for Business Professionals
Resource Type: Book
Resource Requirement: Recommended
Author: Cole Nussbaumer Knaflic
Year: N/A
Edition/Volume: N/A
Publisher: Kindle Edition, Wiley
ISBN: N/A
Chapter/article title: N/A
Chapter/issue: N/A
URL: N/A
Other description: N/A
Source location: N/A
Data Analysis Using SQL and Excel
Resource Type: Book
Resource Requirement: Recommended
Author: Gordon S. Linoff
Year: N/A
Edition/Volume: 2nd Edition
Publisher: Kindle Edition, Wiley
ISBN: N/A
Chapter/article title: N/A
Chapter/issue: N/A
URL: N/A
Other description: N/A
Source location: N/A
Career Ready
Career-focused: No
Work-based learning: No
Self sourced or Uni sourced: N/A
Entire subject or partial subject: N/A
Total hours/days required: N/A
Location of WBL activity (region): N/A
WBL addtional requirements: N/A
Graduate capabilities & intended learning outcomes
Graduate Capabilities
Intended Learning Outcomes
City Campus, 2020, Semester 2, Night
Overview
Online enrolment: Yes
Maximum enrolment size: N/A
Subject Instance Co-ordinator: Ged Kennett
Class requirements
SeminarWeek: 31 - 43
One 3.00 hours seminar per week on any day including weekend at night from week 31 to week 43 and delivered via face-to-face.
Assessments
| Assessment element | Category | Contribution | Hurdle | % | ILO* |
|---|---|---|---|---|---|
Case study (1500 words)Evaluate a case study and answer questions based on it. | N/A | N/A | No | 30 | SILO1, SILO4 |
Data analytics using Excel (2000 word equivalence)Work on a business data set to perform descriptive and diagnostic analytics | N/A | N/A | No | 35 | SILO2 |
Storytelling with data (2000 word equivalence)Turn data insights into visualisations for storytelling. | N/A | N/A | No | 35 | SILO3 |