Year
2023Credit points
10Campus offering
No unit offerings are currently available for this unit.Prerequisites
ITEC617 Modern Database Management
Teaching organisation
150 hours over a twelve-week semester or equivalent study period
Unit rationale, description and aim
The explosion in data and digital technologies has opened new ways of obtaining data-driven insights. To take advantage of these opportunities, organisations need people with the ability to extract, consolidate, analyse and visualise data from very large diverse data sets.
Data analytics refers to a range of computational and statistical techniques used to extract ‘meaning’ (i.e. comprehensible and useable information) from raw data sets. These techniques transform, organise and model the data to draw conclusions and identify patterns of activity that enable organisations to make more-informed decisions about their activities.
In this unit students will learn the foundational concepts in data analytics including a range of computational and statistical techniques used to extract ‘meaning’ (i.e. comprehensible and useable information) from raw datasets. Also, students will learn how to apply data visualisation methods and tools that enable presentation of large volumes of data in a graphical format for decision makers to easily identify underlining patterns. This unit is designed in alignment with Microsoft’s curriculum and provides a pathway to the Microsoft Power Platform Fundamentals certification.
The primary aim of this unit is to equipping students with data analytics and data visualisation knowledge and skills required to design data-driven solutions for solving the real-world problems, and supporting our responsibility to the common good, the environment and society.
Learning outcomes
To successfully complete this unit you will be able to demonstrate you have achieved the learning outcomes (LO) detailed in the below table.
Each outcome is informed by a number of graduate capabilities (GC) to ensure your work in this, and every unit, is part of a larger goal of graduating from ACU with the attributes of insight, empathy, imagination and impact.
Explore the graduate capabilities.
On successful completion of this unit, students should be able to:
LO1 - Recognise business value and various tools and techniques for data analytics & visualisation, and their applications (GA5, GA8)
LO2 - Apply tools for the collection, cleaning, merging and transformation of data (GA5, GA10)
LO3 - Apply data analytics and visualisation tools and techniques to derive useful insights from raw data (GA5, GA10)
LO4 - Evaluate the information needs of organisations and design data analytics and visualisation solutions to support business goals, the environment and society (GA2, GA5).
Graduate attributes
GA2 - recognise their responsibility to the common good, the environment and society
GA5 - demonstrate values, knowledge, skills and attitudes appropriate to the discipline and/or profession
GA8 - locate, organise, analyse, synthesise and evaluate information
GA10 - utilise information and communication and other relevant technologies effectively.
Content
Topics will include:
- Descriptive Analytics
- Predictive Analytics
- Principles and Best Practices in Data visualisation
- Tools for Data Analytics and Visualisation
- Microsoft Power Platform
- Capturing data with Power Apps and Power Automate
- Cleaning and transforming data
- Connecting and merging multiple data sources
- Types of Charts and GraphsData visualisation with Power BI
- Visualising geodata
- Communicating data analysis and visualisation results
- Social and environmental applications of Data Analytics and Visualisation
- Real-world Applications of Data Analytics and Visualisation
Learning and teaching strategy and rationale
This unit is offered in different modes to cater to the learning needs and preferences of a range of participants and maximise effective participation for isolated and/or marginalised groups.
Blended modes
In a blended mode, students will require face-to-face attendance in blocks of time determined by the School. Students will have face-to-face interactions with lecturer(s) to further their achievement of the learning outcomes. This unit is structured with required upfront preparation before workshops. The online learning platforms used in this unit provide multiple forms of preparatory and practice opportunities for you to prepare and revise.
Students should anticipate undertaking 150 hours of study for this unit, including class attendance, readings, online forum participation and assessment preparation.
ACU Online
This unit uses an active learning approach to support students in the exploration of knowledge essential to the discipline. Students are provided with choice and variety in how they learn. Students are encouraged to contribute to asynchronous weekly discussions. Active learning opportunities provide students with opportunities to practice and apply their learning in situations similar to their future professions. Activities encourage students to bring their own examples to demonstrate understanding, application and engage constructively with their peers. Students receive regular and timely feedback on their learning, which includes information on their progress.
Assessment strategy and rationale
To pass this unit, students are required to achieve an aggregate mark of at least 50%. Marking will be in accordance with a rubric specifically developed to measure the level of achievement of the learning outcomes for each item of assessment.
Assessment methods incorporate problem-based tasks, case studies and practical/hands-on tasks that are relevant to the real-world needs. The first assessment provides students with an opportunity to perform various data analytics and visualisations tasks in the lab. In assessment task 2, students will apply the knowledge and practical skills they have gained in the unit to implement data visualisation for a given case study to satisfy the needs of different stakeholders. The aim of this assignment is to equip students with the skills of creating novel data visualisations to effectively reveal the narratives behind the data. Assessment 3 allows students to demonstrate the depth of their knowledge and understanding of data visualisation concepts and tools through Microsoft Certification Exam.
Overview of assessments
| Brief Description of Kind and Purpose of Assessment Tasks | Weighting | Learning Outcomes | Graduate Attributes |
|---|---|---|---|
Assessment 1: Preparatory Exercises This assessment consists of a series of exercises, including data analytics and visualisation using the Microsoft PowerBI, Power Apps, Power Autmate and Power Virtual Agents.. The feedback from this assessment will help students to be ready to apply the concepts in the next assessments. Submission Type: Individual Assessment Method: Practical task Artefact: Program Files | 30% | LO2, LO3, LO4 | GA2, GA5, GA10 |
Assessment Task 2: Certification Exam This assessment task requires student to undertake PL-900: Microsoft Power Platform Fundamental Certification Exam. The exam assesses students’ foundational knowledge of core concepts of data visualisation and how they are implemented using Microsoft Power Platform. Submission Type: Individual Assessment Method: Exam Artefact: Certification | 35% | LO1 | GA5, GA8 |
Assessment Task 3: Data Analytics and Visualisation Case Study In this assignment students will evaluate the information needs of a given case study and produce a proposal for design and implementation of a data analytics and visualisation project detailing the required tools, techniques, visualisation artefacts (charts/dashboards) that provide insightful information that can support decision making and generate value. In their proposal, students also required to demonstrate the application of data visualisation for preservation of the common good, environment and society in the context of the given case study. To ensure academic integrity student are required to present their work in class or record and submit a video presentation. Submission Type: Individual Assessment Method: Practical task Artefact: Written report | 35% | LO1, LO2, LO3, LO4 | GA2, GA5, GA8, GA10 |
Representative texts and references
Albright, SC & Winston, WL 2020, Business analytics: data analysis and decision making, 7th edn, Cengage Learning Inc.
Microsoft Power Platform Fundamentals (https://docs.microsoft.com/en-us/learn/paths/power-plat-fundamentals/)
Mitchell Pearson, Brian Knight, Devin Knight, Manuel Quintana, 2020, Pro Microsoft Power Platform: Solution Building for the Citizen Developer, O'Reilly Media, Inc, USA.