Download our Mobile App
Tableau is one of the most popular data visualisation tools among data scientists and analysts. The tool makes data more accessible to understand for the audience through its inherent visual capabilities. In one of our articles, we showed a hands-on guide on data visualisation by using the free version of Tableau.
In this article, we list down the top 5 ways that can make your graphs look beautiful in Tableau.
(The list is in no particular order)
1| Choose The Correct Chart
While making the data insightful, it is crucial to make sure that you are choosing the correct chart. Charts and graphs help in searching the message in the data and depicting this message of your data to the audience depends on the type of format of the chart and graph you choose.
There are a number of formats that are available in Tableau such as bar, pie, line, bullet, histograms, etc. One should have a basic understanding of when to use particular graphs and charts. For instance, a line graph should be used to display the data that changes in a continuous manner over a period of time while a bar graph should be used while comparing facts in data. And histograms can be used to depict the distributions of variables.
2| Distinguish The Difference By Colours
Colours are a great way to show the difference between the numbers in data as it catches quickly into the eyes. Using bright colours and highlighting the points help in understanding the audience what you actually want to convey through data.
However, there are some limits that one must consider while using colours in a graph. One must play with a single colour and use the variety of shades of the same colour. Using two or more colours can make the chart a little noisy to understand for the audience. For instance, sequential colours can be used to visualise data from high to low, diverging colours can be used to represent the data that diverges from the centre.
Stay ConnectedGet the latest updates and relevant offers by sharing your email.
3| Use of Advanced Chart
There are several popular and traditional charts that have been used by the data analysts for an extended period of time, such as bar graphs, line graphs, pie charts, among others. There are also some of the advanced charts which one must know in order to stand out in a room of data analysts.
- Box plot: A box plot (or box-and-whisker plot) is a diagram of a distribution of data best known for highlighting values such as median, outliers, etc.
- Pareto Chart: A Pareto Chart is a type of chart that contains both bars and a line graph.
- Word Cloud: A Word Cloud is a visual representation of text data.
- Treemap: Treemap is used to display data in nested rectangles. They are a relatively simple data visualisation that can provide insights in a visually attractive format.
- Trellis Chart: Trellis Chart helps in comparing the measures in one concise view across multiple evenly spread rows.
- Bullet Graphs: Bullet Graphs are a variation of a bar graph developed to replace dashboard gauges and meters.
4| Use Predictable Patterns
According to a team of researchers from MIT CSAIL and Adobe Research, knowing where people look and click on visual designs can provide clues about how the designs are perceived, and where the most important or relevant content lies.
While designing a graph or chart, one must follow a symmetrical pattern and always keep in mind to maintain the formats, orders, among others. This will help the audience to understand the insights better than a graph with random patterns and orders.
5| Use Size To Visualise The Values
Size matters in graphs. Using different size to visualise the values in a graph is a great and simple way to create a beautiful and insightful graph. Visualising bigger and smaller shapes and sizes help in understanding the suggestions and points in the graph, making it easier to compare with the rest of the values.
If you loved this story, do join our Telegram Community.
Also, you can write for us and be one of the 500+ experts who have contributed stories at AIM. Share your nominations here.
What's Your Reaction?
A Technical Journalist who loves writing about Machine Learning and Artificial Intelligence. A lover of music, writing and learning something out of the box. Contact: firstname.lastname@example.org