Which Tools Should You Use for Data Visualisation ?
Introduction
Regardless of the sector you work in, you probably have access to lots of data. In the era of big data, we are capable of getting huge amounts of information in real time: sales numbers, website traffic, etc.
This data is often very rich, so long as you know how to exploit it. To get the full potential from a database, nothing is as effective as data visualisation. This method lets you create a visual support that will help with decision-making and communication. It has become the go-to method for those who analyse data.
In this article, ALLONIA will help you to choose the best tool to visualise and make sense of your data.
What is data visualisation ?
Some key definitions
Data visualisation, or dataviz, consists in presenting a dataset in a visual format. In other words, data visualisation is when you present data in a graph rather than in a chart that is hard to understand.
Data visualisation techniques use only quantitative data, which is data that can be counted, such as the number of sales, or the time to respond to an email.
Dataviz is an essential branch of data analysis. Indeed, presenting information in a graph helps quickly draw out trends. For example, if the number of sales is displayed on a timeline, it’s possible to quickly conclude that sales are increasing or decreasing.
Visualisation and data analysis
A database is like a goldmine. To exploit its potential, it’s essential that you study the links between data; in other words, you have to analyse data.
Data analysis will help extract useful information for making decisions and influencing future company performance. For example, analysing a website’s traffic helps identify the pages that are least visited, and thus those that need improvement.
Over the course of analysis, data visualisation is a very powerful tool. It offers visual support to highlight certain markers, to follow evolution, or to identify anomalies very quickly.
Moreover, graphs help to communicate and share information in a clearer and more impactful way. Data visualisation is thus particularly useful when sharing information with your teams: a graph is often very effective in supporting your message.
The main types of visualisation
There are many types of visualisation to help present data in a clear way. To make your visualisation impactful, you need to carefully choose the appropriate format and colours for your data and goals.
Here are some of the most common types of visualisation:
- For statistical or frequency distribution, it is best to use a whisker box or clouds and words
- For an evolution, use a curve or a bar chart
- For proportions or distribution, use a pie chart or a proportional map
- For the evolution of a proportion, use stacked curves or stacked bar charts
- For a network or the relations between various variables, use a traffic map or arc diagram
For localisation or concentration, use a geographical map.
What are the most popular visualisation tools ?
Here are some of the most used visualisation tools, with their functions and characteristics.
Excel
You probably already know Excel, it’s an essential software that lets you display tables of data and visualise them in the same spreadsheet. Google has a similar online tool, called Google Sheets.
Metatitle: An example of a graph on Excel
Pros: it’s very easy to import data, and to modify and regroup it with simple calculations.
Cons: the available graph formats are limited and sometimes unappealing. Excel isn’t only used for dataviz, it has many functions and can be hard to handle.
Tableau Software
Tableau software is a go-to tool in data visualisation. Made only for dataviz, this tool is widely used because it is so intuitive. It has a wide variety of graphs and it is very easy to make a dashboard with your choice of infographics.
Metatitle: example of data visualisation with Tableau Software
Pros: Tableau Software lets you easily update your data, with associated visualtions, to let you follow the latest trends.
Cons: the software is rather expensive.
Google’s tools
Google a range of data visualisation tools. Specifically, Google Data Studio uses web data to produce graphs, and Google Charts lets you make a variety of visualisations.
Metatitle: making a pie chart with Google Charts
Pros: Google’s tools offer many types of visualisation that can be personalised.
Cons: you need to be familiar with coding if you want to change an existing model on Google Charts.
Power BI
Developed by Microsoft, Power BI is a simple tool to use. You just need to integrate data, and then click on the type of graph you want to use. The visuals are automatically generated, and can be personalised.
Metatitle: Various data visualisation options on Power BI
Pros: Power BI is very interactive and easy to use. It lets you create elegant reports that are easy to share
Cons: it is hard to group and modify data, and the in-depth analysis tools are limited.
Summary
Regardless of costs, hers is a summary of the various characteristics of the data visualisation tools.
| Ease of use | Interactivity | Variety of graphs | Large amount of data supported | Ease of updating data automatically | |
| Excel | + + | – – | – – | No | No |
| Google sheet | + | – | – – | No | Yes |
| Power BI | – – | + + + | + + | No | Yes |
| Tableau Sofware | – – | + | + + | Yes | Yes |
| Google data studio /Google Charts | + + + | + + | + + + | Yes | Yes |
How to choose the appropriate data visualisation tool
Properly identify your needs
Visualisation tools offer different possibilities, which are more or less adapted to your needs. Most importantly, you need to know what your objectives are and which visualisation types you need:
- If you have identified multiple needs, you should use multipurpose tools.
- If you have a specific need, a niche tool specialised in the type of data you have is more appropriate.
Use cases of each tool
Each data visualisation tool has its specialties. For example, if you want to create a dashboard that updates every day and is visible to all collaborators, Tableau, Power BI, or Google Data Studio are the right tools for you.
To choose the right tool, you should ask yourself the following questions:
- What type of data do you use? How much data is there?
- Do you wish to update your data in real time?
- Which type of visualisation do you want? How many variables are you looking for?
- Do you need specific graphs?
- How many people will be working with this tool? How experienced are these people in dataviz?
- What are your data protection policies?
Answering these questions will help you eliminate options and find the right tool.
To find out more about ALLONIA
ALLONIA: the SaaS artificial intelligence platform that accelerates and secures AI projects for large companies, SMEs, ETIs and public organisations.
ALLONIA is the AI platform that enables companies to develop, deploy and exploit machine learning (ML) models in a secure and collaborative way.
ALLONIA enables you to deploy your AI projects in just a few clicks and makes it easy to share your data and models between your internal teams, as well as with your partners and customers.
Conclusion
Don’t overlook dataviz! Today, it is an essential discipline for improving your performance and developing your future strategies. It’s no longer possible not to make the most of the data you have at your disposal, especially as visualisation tools are becoming more and more numerous and easier to use.
If you would like to find out more about the use of data and explore our solutions, please visit www.allonia.com.