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Big Data: Data Visualisation

Data visualisation is vital in bridging the gap between data and decisions. Discover the methods, tools and processes involved.

45,746 enrolled on this course

  • Duration

    3 weeks
  • Weekly study

    2 hours

Data visualisation is an important visual method for effective communication and analysing large datasets. Through data visualisations we are able to draw conclusions from data that are sometimes not immediately obvious and interact with the data in an entirely different way.

This course will provide you with an informative introduction to the methods, tools and processes involved in visualising big data. We will also take the time to examine briefly the use of visualisation throughout history dating back as far as 17000 BC.

Skip to 0 minutes and 7 seconds Hi everyone and welcome to our Big Data Analytics collection of courses. My name is Kerrie Mengersen. Imagine you’re a scientist in a lab, investigating a new strain of bacteria that’s extremely harmful and potentially deadly. As a scientist you’re naturally curious, however there’s no way you would want to get too close to the bacteria and risk being contaminated. So how can you examine these bacteria closely, without potentially risking your health? Real life situations such as this have been resolved through the use of visualisations. Instead of physical interaction with the bacteria, scientists have created a virtual playground where they can effectively interact and examine bacteria without being at risk.

Skip to 0 minutes and 55 seconds Creating good visualisations not only produces something that looks nice, it helps us uncover and interact with information that might not have been immediately obvious. In this course we offer a unique insight into different visual techniques for analysing Big Data. We help you understand some different tools for creating effective visualisations, and show you examples where visualisations have been incredibly effective - such as the bacteria example. We’ve created this course to share with you the multi-lensed approach we use at ACEMS that enables us to create new insights and ways of thinking around the Big Data space. We’re excited and we hope you are too.

What topics will you cover?

  • Introduction to visualisation
  • Information visualisation
  • Scientific visualisation
  • Visualisation tools
  • Design approaches for visualisation
  • Visualisation for communication

Learning on this course

On every step of the course you can meet other learners, share your ideas and join in with active discussions in the comments.

What will you achieve?

By the end of the course, you‘ll be able to...

  • Explore big data frameworks
  • Demonstrate an integrated approach to big data
  • Develop an awareness of how to participate effectively in a team working with big data experts

Who is the course for?

We have designed the course for people from different fields who want to learn how to produce visualisations that help us better understand real-world big data problems. You will gain the most from the practical exercises if you are comfortable with computer programming however you don’t need to have any prior experience using the software listed below.

What software or tools do you need?

We will use a variety of tools so that you become comfortable engaging with different software and confident trialing new packages to find those that best meet your needs. Please review the product websites below to ensure your system meets the minimum requirements for the tools we will be using.

  • Tableau: You can use the free trial for a period of 2 weeks. Please do not start the trial until you are ready to do the Tableau exercises.
  • MATLAB Online: MathWorks will provide you with a license to use MATLAB online for the duration of the course.
  • D3.js: The D3 JavaScript library is available under BSD license.

You can still learn effectively even if you don’t have access to all of these tools as you will be able to see what they can do for you.

Who will you learn with?

I'm A/Professor (QUT & UNSW) and Team Leader (CSIRO/Data61), active in big data visualisation and analytics, computational and simulation sciences, computer graphics and interactive techniques.

I'm a Postdoctoral Fellow in the ARC Centre of Excellence for Mathematical and Statistical Frontiers at QUT. I'm interested in numerical simulation of physical systems, gpu computing and visualisation

Who developed the course?

Queensland University of Technology

QUT is a leading Australian university ranked in the top 1% of universities worldwide by the 2019 Times Higher Education World University Rankings. Located in Brisbane, it attracts over 50,000 students.

  • Established

  • Location

    Brisbane, Australia
  • World ranking

    Top 180Source: Times Higher Education World University Rankings 2019

Endorsers and supporters

content provided by

ARC Centre of Excellence for Mathematical and Statistical Frontiers

supported by


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  • Complete 90% of course steps and all of the assessments to earn your certificate

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