Business Analytics Foundations (BSAN7205)

Module 1.1: The Data Race Framework

This topic builds on a practical framework called Data Race to explain how businesses can create value from their digital data assets.

Live Welcome Session: This session will focus on staff and student introductions, outlining course objectives, reviewing assessments, and discussing the Data Race Framework.

Self-directed learning: Students need to complete this week's self-directed material before the live session.

Learning outcomes: L01

Module 2.1: Business Purpose

This topic focuses on how companies can formulate analytics business cases, using a user-centric approach.

Live Case Analysis Session: This case analysis session focuses on the journey of IDEO, a design thinking firm, and how their approaches can be used to develop user-centric analytics solutions.

Preparation: Students need to read and analyse the case study before the live session and discuss it with their peers on the discussion board.

Learning outcomes: L01

Module 2.1: Business Purpose (continued)

The focus on this week is to progress the project work and unpack the business problem.

Live Industry Session: The session gives students opportunity to ask assignment-1 data related questions to Aginic employees.

Self-Directed Learning: Students need to work on assignment 1 and prepare questions for the industry session.

Learning outcomes: L01

Module 3.1: Understanding Data

This topic takes a deep dive into understanding data, its evolution, data sources and types, data's quality issues and meta data.

Live Case Analysis Session: This session provides a discussion on the cases of Netflix and Walmart and how they explore their data assets to generate value for users.

Self-Directed Learning: Students need to complete this week's self-directed material before the live session.

Learning outcomes: L02

Module 3.1 (Continued): Coding Bootcamp Prep

This topic uses a hands-on programming approach to demonstrate how data can be explored and transformed to make it fit for use.

Live Coding Bootcamp Session (Prep): This session will introduce you to the Python coding environment in Jupyter Notebook.

Self-Directed Material: Students need to complete this week's self-directed material before the live session.

Learning outcomes: L02

Module 3.1 (Continued): Generative AI for coding

In this session, students will be introduced to generative AI and how it can be used for coding using prompt engineering.

Live session: Students will learn how to generate code using generative AI and how to evaluate the accuracy of the code.

Self-Directed Material: Students need to complete this week's self-directed material before the live session.

Learning outcomes: L02

Module 3.2: Exploring Data (Coding Bootcamp 1)

This module introduces you to techniques to identify and address data quality issues in your data.

Live Coding Bootcamp Session: This session will introduce you to how to explore data using Python.

Self-Directed Learning: You will need to work through the self-directed learning material for this module.

Learning outcomes: L02

Module 3.2 (Continued): Coding Practice 1a

This session is to help you practice your coding skills and troubleshoot any errors.

Learning outcomes: L02

Module 3.2 (Continued): Coding Practice 1b

This session is to help you practice your coding skills and troubleshoot any errors.

Learning outcomes: L02

Module 3.3: Transforming Data (Coding Bootcamp 2)

Module 3.3 is the final topic for the second step in the Data Race, focusing on Transforming Data.

Live Coding Bootcamp Session: This session is a coding bootcamp focusing on using Python for data transformations.

Self-Directed Learning: You will need to work through the self-directed learning material for this module.

Learning outcomes: L02

Module 3.3 (Continued): Coding Practice 2a

Learning outcomes: L02

Module 3.3 (Continued): Coding Practice 2b

Learning outcomes: L02

Module 4.1: Performance Management (Coding Bootcamp 3)

This Module describes how data and analytics can help companies manage their business performance.

Live Coding Bootcamp Session: This session is a coding bootcamp focusing on using Python for generate insights from the data.

Self-Directed Learning: You will need to work through the self-directed learning material for this module.

Learning outcomes: L02

Module 4.1 (Continued): Coding Practice 3a

This session focus on data exploration and transformation using Python.

Learning outcomes: L02

Module 4.1 (Continued): Coding Practice 3b

This session is to help you practice your coding skills and troubleshoot any errors.

Learning outcomes: L02

Assessment 2 Q&A Session 1a

This session will help you practice your coding skills and prepare for Assignment 2 submission.

Learning outcomes: L02

Assessment 2 Q&A Session 1b

This session will help you practice your coding skills and prepare for Assignment 2 submission.

Learning outcomes: L02

In-Semester Break

Module 4.2: Introduction to Machine Learning

This topic explains the process of machines learning, together with a number of machine learning algorithms and how they are used in business.

No Live Session due to public holiday.

Self-Directed Learning: You will need to work through the self-directed learning material for this module.

Learning outcomes: L02

Module 4.2 (Continued): Dashboarding workshop 1a

This session provides a hands-on experience to build digital dashboards with a popular tool.

Learning outcomes: L02

Module 4.2 (Continued): Dashboarding workshop 1b

This session provides a hands-on experience to build digital dashboards with a popular tool.

Learning outcomes: L02

Module 4.3 & 4.4: Visual Storytelling and Data-driven Action

This topic shows how analytics professionals can build effective narratives that influence their audience and inspire competitive action or automation of business processes.

Live Session: This session will focus on trust in data and how best inspire action based on data-driven insights.

Self-Directed Learning: You will need to work through the self-directed learning material for this module.

Learning outcomes: L02

Module 4.4 (Continued): Dashboarding workshop 2a

Learning outcomes: L02

Module 4.4 (Continued): Dashboarding workshop 2b

Learning outcomes: L02

Module 5.1: Value

This module explains how analytics value can be defined and measured and how its negetive consequences can be avoided.

Live session: This session will discuss the Guess case study and how they measured analytics value. It will also involve a discussion of surveillance captalism By Shoshana Zuboff.

Self-Directed Learning: You will need to work through the self-directed learning material for this module.

Learning outcomes: L01, L02, L03

Module 5.1 (Continued): Dashboarding workshop 3a

This session provides a hands-on experience to build digital dashboards with a popular tool.

Learning outcomes: L02, L03

Module 5.1 (Continued): Dashboarding workshop 3b

Learning outcomes: L02, L03

Module 6.1: Becoming Data Savvy

This is a revision week and will include Q&A session for Assignment 3.

Learning outcomes: L02, L03

Module 6.1: Becoming Data Savvy

This is a revision week and will include Q&A session for Assignment 3.

Learning outcomes: L02, L03

Module 6.1: Becoming Data Savvy (Continued)

This is a revision week and will include Q&A session for Assignment 3.