ITEC202 - Data Management and Visualisation

Year

Credit points

Campus offering

Prerequisites

ITEC200 Data and Information Management

Incompatible

DATA201 Data Analytics and Visualisation , ITEC300 - Data Visualisation

Teaching organisation

150 hours over a twelve-week semester or equivalent study period

Unit rationale, description and aim

The increasing use of digital technologies has resulted in generation and storage of vast amount of data. Data needs to be processed to provide valuable insights that enable improved decisions, processes, products or services. Hence, increasingly, organisations need people with the ability to extract, consolidate, analyse data from diverse sources and present information generated from data in an insightful manner, such as visualisations.

In this unit you will learn the skills in data management and visualisation to capture, store, model, transform, analyse and visualise data to extract ‘meaning’ (i.e., comprehensible and useable information) from raw datasets. Also, you will learn how to apply data visualisation methods and tools that enable presentation of large volumes of data including geodata 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 equip students with the data management and data visualisation knowledge and skills required to solve the real-world data problems, including data-driven solutions to support 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 - Describe business value and various tools for data management, analytics & visualisation, and their applications (GA5, GA8)

LO2 - Integrate existing data from multiple sources into a single store using a scalable data service and build no-code apps for data entry (GA5, GA10)

LO3 - Apply data management and visualisation tools and techniques to derive useful insights from raw data (GA5, GA10)

LO4 - Create intelligible and insightful data visualisation artefacts such as charts and dashboards to support our responsibility to the common good, 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:

• Data visualisation concepts and principles
• Introduction to Microsoft Power Platform Creating data-driven apps in Microsoft Power Apps for capturing data
• Managing data using Microsoft Dataverse
• Prepare Data for Analysis
• Model Data in Power BI
• Visualise data in Power BI
• Data Analysis in Power BI
• Connecting and merging multiple data sources
• Different types of data visualisations and their purpose
• Reports and dashboards
• Visualising geodata
• Microsoft Power Automate
• Microsoft Power Virtual Agents
• Social and environmental applications of Data Analytics and Visualisation

Learning and teaching strategy and rationale

This unit is offered in two different modes (“Blended” mode and “Online” mode) to cater to the learning needs and preferences of a range of participants and maximise effective participation for isolated and/or marginalised groups.

Blended Mode

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 students to prepare and revise.

Online Mode

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.

Students should anticipate undertaking 150 hours of study for this unit, including class attendance, readings, online forum participation and assessment preparation.

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 equipment 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 database technology concepts and tools through Microsoft Certification Exam.

Overview of assessments

Representative texts and references

Microsoft Power Platform Fundamentals (https://docs.microsoft.com/en-us/learn/paths/power-plat-fundamentals/)

Microsoft Certified: Data Analyst Associate (https://docs.microsoft.com/en-us/learn/certifications/data-analyst-associate/ )

Mitchell Pearson, Brian Knight, Devin Knight, Manuel Quintana, 2020, Pro Microsoft Power Platform: Solution Building for the Citizen Developer, O'Reilly Media, Inc, USA.

Deckler, G. & Powell, B. 2021, Microsoft Power BI Cookbook: Gain expertise in Power BI with over 90 hands-on recipes, tips, and use cases, 2nd Edition, Packet Publishing.

O'Connor, E 2019, Microsoft Power BI Dashboards Step by Step, 1st edition. Microsoft Press.

Albright, SC & Winston, WL 2020, Business analytics: data analysis and decision making, 7th edn, Cengage Learning Inc.