VCE Data Analytics Resource Page

A resource for Heathmont College students studying VCE Applied Computing - Data Analytics Unit 3 & 4.

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Data Visualisations

Overview

Data Visualisation Image - Created by ChatGPT 4o

Data visualisation helps convey complex information clearly. This section covers types of visualisations, best practices, and how to use tools like Matplotlib or Plotly to create visualisations from data, showcasing our results in Streamlit. You will learn about the purposes of data visualisations, design tools, and formats to improve their effectiveness for intended users.

Data Visualisations in the Study Design

Unit 3 Outcome 1

Key Knowledge:

Key Skills:

Purposes of Data Visualisations

Exploratory Data Analysis

Exploratory data analysis (EDA) is the process of analyzing data sets to summarize their main characteristics, often using visual methods. EDA is an essential step in the data analysis process, as it helps identify patterns, trends, and anomalies in the data.

When performing EDA, the visualisations are often only seen by the data analyst. The goal is to understand the data better and prepare it for further analysis or modeling.

In Data Analytics, we have engaged in EDA when using Excel to create histograms and scatter plots to help us identify trends and relationships in the data. These visualisations give us a better understanding of the data as well as helping us identify any outliers or anomalies that may need to be addressed before further analysis.

Presentation of Information

The presentation of information is the process of creating visualisations that effectively communicate data insights to a wider audience. This can include stakeholders, clients, or the general public. The goal is to present the data in a way that is easy to understand and interpret. The way information is presented can vary depending on the audience and the context.

For example, a data visualisation intended for a technical audience may include more complex charts and graphs, while a visualisation for a general audience may use simpler visuals and more straightforward language. In presenting information, it is important to consider the audience’s level of understanding and familiarity with the data. If the variables are already understood by the audience, then the visualisation can be more complex. However, if the audience is not familiar with the data, it is important to use simpler visuals and provide clear explanations.

Providing Interactive Experiences

Interactive data visualisations allow users to explore data in a more engaging way. This can include features such as filtering, zooming, and hovering over data points to see more information. Interactive visualisations can help users better understand the data and draw their own conclusions.

Because the user is interacting with the data themselves, they have greater control over the visualisation and can explore the data in a way that is most relevant to them. It also means that the visualisation needs to be designed in a way that is intuitive and easy to use. This can include features such as tooltips, legends, and clear labels to help users understand what they are looking at.

Types of Data Visualisations

Infographics

Infographics are visual representations of information, data, or knowledge. They are designed to present complex information quickly and clearly. Infographics can be static or dynamic, and they often combine text, images, and graphics to convey a message. Infographics are often used in marketing, journalism, and education to present information in a visually appealing way.

Infographics stay away from complex charts and graphs, instead using simple visuals and clear explanations to convey the message. They are often used to tell a story or present a specific point of view.

They can be used to present a wide range of information, from statistics and data to historical timelines and processes. Infographics are often shared on social media or used in presentations to engage the audience and make the information more memorable.

Dashboards

Dashboards are visual displays of data that provide an overview of large or related datasets. They are often used in business intelligence and data analytics to monitor performance and track progress toward goals. Dashboards can be interactive or static, and they can include a variety of visualisations, such as charts, graphs, and maps.

Dashboards are designed to provide a quick and easy way to understand complex data. They highlight the most relevant data points and trends, then allow users to drill down further into the details if needed.

Dynamic Data Visualisations

Dynamic data visualisations are interactive visualisations that update in real-time or near real-time: either from live data or through user interaction. They allow users to explore data as it changes, providing a more engaging and informative experience. Dynamic visualisations can include features such as live data feeds, animations, and interactive elements that respond to user input.

Dynamic visualisations are often used in applications such as financial dashboards, social media analytics, and real-time monitoring systems. They can help users identify trends and patterns in the data as they emerge, allowing for more informed decision-making.

Design Tools for Representing Data Visualisations

Mock-Ups

Mock-ups are visual representations of a design or concept. They are often used in the early stages of the design process to communicate ideas and gather feedback. Mock-ups can be created using various tools, including graphic design software, wireframing tools, or hand-drawn sketches.

Mock-ups are not intended to be functional; instead, they focus on the visual aspects of the design. They can include elements such as layout, color schemes, typography, and imagery. Mock-ups help designers visualize how the final product will look and feel, allowing for adjustments before moving on to the development stage.

Storyboards

Storyboards are visual representations of a sequence of events or actions. They are often used in the planning stages of a project to outline the flow of information and how different elements will interact. Storyboards can include sketches, images, and text to convey the narrative and structure of the visualisation.

Storyboards help designers and developers visualize the user experience and identify potential issues before creating the final product. They can be used to plan everything from infographics to interactive dashboards, ensuring that the final design effectively communicates the intended message. They could even be used to identify the visual hierarchy of the visualisation, such as which elements are most important and how they should be arranged.

Formats and Conventions Applied to Data Visualisations

Use of Colours, Fonts, Images, and Icons

The use of colours, fonts, images, and icons in data visualisations is crucial for conveying information effectively. These elements can help create a visual hierarchy, guide the viewer’s attention, and enhance the overall aesthetic of the visualisation.

Visual Hierarchy, Use of Conventions and Clarity of Message

Techniques for Testing Data Visualisations

Visual Inspection of the Appearance of the Data Visualisation

Testing data visualisations through visual inspection involves reviewing the visualisation for clarity, accuracy, and overall effectiveness. This can include checking for:

Confirming that Charts and Graphs are Representative of the Data Being Visualised

It is essential to ensure that the charts and graphs accurately represent the data being visualised. This can include checking for:

Learning Resources