According to reports from Gartner, more than 40 per cent of data science tasks will be automated by 2020. And with automation driving data collection and grouping, it has become cheaper and easier for businesses to gather information.
However, the sheer amount of data being collected means that it’s difficult for businesses to translate that information into an accessible and presentable form. Poring over spreadsheets trying to analyse trends and patterns can be a difficult process. This is where data visualisation tools can be vital.
What is data visualisation?
Data visualisation is simply the graphical representation of information. Using elements such as graphs, maps and charts, data scientists can better understand patterns and trends from a business’ data. Through visualisation, data scientists are able to make these findings accessible and easy to understand for all key stakeholders across a business.
Colours and patterns naturally attract the human eye, allowing data visualisation to aide analytical interpretations more easily. Essentially a graphic form of storytelling, visualisation tools can help team members understand not only what the data is, but what it means.
Some of the visual elements used in data visualisation include:
- Infographics – a picture that uses words and graphics to explain information in an engaging way
- Dashboards – information tools that visually track, analyses and displays KPIs
- Area charts – a graphical display of quantitative data based on a line chart
- Bar charts – graphically presenting categorical data with rectangular bars that represent certain values
- Bubble charts – visualising data through multiple circles, in a ‘scatter plot’ variation
What tools can be used for data visualisation?
Used by many large organisations such as Barclays, Pandora and Citrix, Tableau is a useful tool for presenting business’ data visually. This powerful and secure software allows you to present visually engaging analytics by connecting a variety of data sources, displaying the information as a ‘story’.
This video explains how Tableau can be used:
Datawrapper is a visualisation tool predominantly used in the publishing industry. The Wall Street Journal, Twitter, The Guardian, Buzzfeed and The Washington Post all utilise Datawrapper’s data visualisation capabilities. It enables users to create and publish charts or maps, making it perfectly suited to fast-moving work environments like a newsroom.
Plotly is an incredibly fast and user-friendly way for data scientists to showcase insights gleaned from data simulations. Its slick charts and user interface are used by organisations such as Google, New York University, Goji and even the United States Air Force.
This visual content service utilises a native dedicated big data visualisation service that can be a very useful business tool. Connected with a creative visual team, data scientists who use Visual.ly can receive project milestones to help keep track of their work.
The service also offers a distribution network to showcase data projects. Visual.ly’s impressive portfolio includes VISA, Nike, The Huffington Post and The National Geographic.
Chart.js is a visualisation tool that can be particularly useful for small chart projects. It’s open-source, fast and easy to use, and can distribute information in a variety of charts.
Using a HTML5 canvas, this service is fantastic for data scientists looking to undertake smaller projects for their business.
How can visualising data inform business decisions?
Demonstrating useful, actionable data insights is not just as simple as presenting an attractive graph or chart to your team. Successful data visualisation will highlight the right information and make it interesting, while still delivering the necessary business messages.
This combination of analysis and visual storytelling is important when communicating requisite information to team members, offering them the data they need to succeed in their job. By understanding trends and patterns, actionable insights can help a business better forecast where it’s moving, while also updating relevant KPIs.
These visualisations can also help a business understand how it operates internally, which can increase profitability and help optimise the performance of team members. Visual representations of data can also help understand customer preferences, which can guide further development of popular products.
Effective data visualisation helps businesses make real decisions based on real data. At James Cook University, data visualisation is one of the core units taught in their online Master of Data Science.
The Data Visualisation unit at JCU focuses on Tableau, offering a detailed understanding of data visualisation techniques, from gathering the data to techniques to communicate effectively key insights to key stakeholders.