Advanced Visualisations in Tableau

Tableau is a robust business intelligence (BI) and data visualisation platform that lets users connect to multiple data sources, make shareable and interactive dashboards, and extract insights from their data. Tableau is widely used in various industries and organisations to analyse, visualise, and comprehend complex datasets.

Numerous data sources, such as databases, spreadsheets, cloud-based data, and web data connectors, can be connected to Tableau. In addition to data extracts for offline analysis, it supports live connections. Tableau offers data transformation, shaping, and cleaning tools. To better meet their needs for analysis, users can modify and organise their data. Tableau provides a drag-and-drop interface to enable the creation of a wide range of interactive visualisations, such as maps, bar charts, line charts, scatter plots, and more. Users can easily customise the appearance of visualisations.

The version of Tableau Used

Tableau Public is a free version of Tableau, which is available on the official website of Tableau. This version of Tableau provides a variety of features, including creating dashboards and stories and utilising different forms of data files like CSV, text, Excel and many others. It gives access to almost all of the features of the software. The Tableau public offers a drag-and-drop feature to add features in order to make interactive charts and graphs. It provides high-performance visualisation and various advanced visualisation options. The main difference is that this version is less secure than the other paid versions, as workbooks go public when the user saves them. Moreover, it gives limited data availability compared to other paid versions of the Tableau.

Visualisations with Tableau

Tableau provides a huge variety of charts and graphs, which helps to visualise and analyse the data to get insights from them. The most basic visualisations made with tableau are:

• Bar Chart
• Heat Map
• Histogram
• Pie Chart
• Gantt Chart
• Line Chart
• Box Plot
• Scatter Plot

There are many other basic charts and graphs made with the help of Tableau. The additional feature of Tableau is that it offers the ability to create advanced visualisations (charts or graphs), which help analyse the data in a better and more effective way.

The following article guides about different advanced visualisations in Tableau, the process and steps for creating them and the uses of each graph and chart.

Here is the list of the most effective advanced visualisations made using Tableau:

1. Donut Chart
2. Word Clouds
3. Lollipop Charts
4. Nested Bar Charts
5. Pareto Charts
6. Area Charts
7. Radial Charts
8. Bullet Chart
9. Waterfall Charts
10. Motion Charts

Donut Chart

A Donut Chart is a type of pie chart but with a hole in the centre. In donut charts, cumulative data can be added, which may show different categories in pie charts. Basically, a donut chart is a hollow circular chart that has an empty space in the centre and the labels can be added in between the donut. These labels show the values which are used for comparing the segments.

Method to create Donut Chart

To make a donut chart, there is a need for two different pie charts. The most simple dataset that can be used for working in Tableau is Sample-Superstore. It is in the form of xls, which provides different details about different products like sales, profit, category, subcategory, etc.

Steps for donut chart:

Step 1: Create pie charts

• In the rows section, write AVG(0) and click enter.
• Again, write the same command.
• As a result, it gives 2 different axes in the workbook.

Step 2: Modifying Pie Chart 1

• Click on the first feature AVG(0) in the Marks section.
• Choose the pie chart from the drop-down menu of the Marks section.
• Add the 'Category' dimension in the Color card in the Marks section.
• Now, add the 'Sales' to the Angle card (One can choose different dimensions like profit, discount, etc.)
• For better analyses, add the 'Sales' to the label card.

Users can make different changes, like adding more features to it, like sub-categories, discounts, etc., or a percentage of any feature, which can also be displayed using the Quick Table Calculation section.

Step 3: Modifying Pie Chart 2

• Click on the second feature 'AVG(0).
• Choose the Circle chart from the drop-down menu. It will make a circle.
• Change its colour to white. This will make the hole in the donut chart.
• Now, add the 'Sales' feature to the Labels card.

Step 4: Combining both charts to make the donut chart

Right-click the second feature AVG(0) in the row section, and click the 'Dual Axis'. Then, adjust the size of the white circle for a better understanding and look.

This is how the donut chart will look like:

Word Cloud

A word cloud is a visual display of textual data that highlights the most frequently occurring words or phrases within a particular dataset. Another frequent name for it is a tag cloud. The most important keywords or tags from a website are frequently shown in this kind of chart, where the size and colour of each word indicate how frequently or how important it appears in the data. Stated differently, word clouds offer a graphical representation of the most prevalent terms or topics present in a specific collection of text or information.

Method to create Word Cloud

Step 1: Choosing appropriate features

• For a word cloud, a categorical variable and a numerical variable are needed.
• Here, the 'Region' and 'Sub-category' features are used as categorical values. The 'Sales' feature is used as the numerical variable.

Step 2: Selecting the cards in the Marks section

• Drop the Region to the text and colour card.
• Move the Sales to the size card.
• To make it more interactive, add more categorical values to the text card; here, a sub-category is added to the text card.

As an output, it will give a heat map containing different sections in different colours.

Step 4: Converting the heat map to the word cloud.

Change the 'Automatic' drop-down menu to the 'Text' one. It will give a word cloud focussing on the keywords of the data features chosen, differentiated by different colours and sizes.

This is what a word map looks like:

Nested Bar Charts

A nested bar chart, which is also sometimes referred to as a stacked bar chart, is a graphical representation of data that consists of multiple bar segments stacked on top of each other. This type of chart is commonly used to show the relationship between different categories or groups. In a nested bar chart, each bar represents a different category, and the length of each segment within the bar indicates the contribution of a specific sub-category to the overall total. By using a nested bar chart, it is easy to compare and contrast the contributions of different sub-categories within each category, making it a useful tool for data analysis and visualisation.

Method of Creating Nested Bar Chart

Step 1: Make a detailed bar chart

• Add the 'Category' and 'Sub-Category' features to the rows section.
• Include "Measure Values" in the section on columns. Maintain the Sales, Profit, and Discount figures in the measure.

Step 2: Modifying the bar chart to create a stacked appearance

• To display bars of various sizes based on the value, add the "measure names" to the "Size" card in the Marks section.
• Now, update the "Colour" card with the "measure names." Modify the colour scheme to improve visibility and comprehension.

Step 3: Modify the layout

• Turn off the "Stack Marks" option by going to the analysis option.
• Adapt the bars' size accordingly.

The Nested Bar Chart looks like this:

Pareto Chart

An 80/20 rule, also referred to as the Pareto Principle, is illustrated graphically in a Pareto chart. It is a graphical representation of the relationship between causes and effects that combines a bar chart and a line chart. About 80% of the effects result from 20% of the causes, according to the Pareto Principle. A Pareto chart shows that a small number of categories account for the majority of the total, with the remaining categories having a much smaller influence. Using the chart, the most important contributing factors are determined and given priority for improvement.

Process to make Pareto Chart

Step 1: Creating a bar chart

• Add the 'Sales' to the rows and the 'Sub-Category' to the columns.
• Sort the Sub-category by choosing the Sort option.
• Choose the Descending option in Sort order.
• Choose Field in the Sort by option.

As a result, it will give the bar chart in the Descending format (from highest sales to lowest).

Step 2: Add a line chart

• Drag the Sales features to the right side of the window till a dotted line appears.
• Click the SUM(Sales) (2) and choose the Line type in the marks card.

As a result, it will give a bar chart following a line chart at the top ends of the bars.

Step 3: Formatting the Pareto Chart

• Click on the Add Table Calculation option from the second SUM(Sales) attribute present on the row pane.
• Now, add the running total to the primary calculation table of the SUM(Sales).
  • Select the Running total as the Calculation type.
• Next, Add the secondary calculation and select the Present of Total.

It will change the position of the line chart placed on the bar chart.

Step 5: Adjusting the Pareto Chart

• Change the colour of the line chart and the bar chart from the Colours Section of the Marks Card.

The resultant Pareto Chart is:

Area Chart

An effective tool for visualising quantitative data over a given time periods is an area chart. It's a great way to see the cumulative total of several different data series and how each one affects the total. The purpose of the chart is to show coloured regions that lie between each data series' line and the axis. This gives each component's relative proportions a clear visual representation. A better grasp of the trends and patterns in the data is provided by the shaded areas, which make it simple to see how each data set changes over time and how it affects the total.

The process of making an Area Chart

Step 1: Adding features to the base chart

• Add the 'Order Date' to the column section.
• Choose the Month option from the drop-down option, which shows the Date in the month format. (MONTH(Order Date)).
• Now, add the Quantity to the rows.

It will give a line chart.

Step 2: Adjusting Marks Card

• Change the drop-down menu of Marks card to Area.
• Add Ship Mode to the colour card.
• Add region to the label card
• Add Subcategory to the detail card.
• Now, change the colour to make it more interactive.

Here is the resultant Area Chart:

Bullet Chart

A bullet chart is a graphical data representation used to show the progress of a single metric, like sales or revenue, towards a particular target or goal. Compared to conventional bar charts, this kind of bar chart was created expressly to offer more context and detail. Bullet charts are a useful tool for performance tracking and analysis because they make it easy for users to determine whether a metric is on track to meet goals by using color-coded ranges and markers.

Method to create Bullet Chart

• Add Profit measure to the column section.
• Add Sub-category to the row section.
• Add Sales to the label option of the marks card.
• Choose the bullet graph from the Show Me section.
• The Discount measure can also be added to the label card for more detailing.

Here is the final Bullet Chart:

Lollipop Chart

A lollipop chart is a special form of facts visualisation that effectively blends the elements of a dot plot and a bar chart. Displaying personal records points with their distribution or common values is a commonplace application for this powerful tool. A vertical line typically called the 'lollipop stick', which represents a numerical axis, makes up the chart. A circular marker or dot designating a particular fact point appears at the end of every line. In this way, by emphasizing users' values and displaying their distribution and shape, the lollipop chart gives a clean, visible depiction of complicated data sets.

How to Make a Lollipop Chart?

Step 1: Base of the Lollipop Charts

• Add the 'Region' and the 'Category' feature to the Columns section.
• Add 'Sum(Profit)' to the rows section.
• Duplicate the 'Sum(Profit)' feature in the rows section.

As a result, it gives 2 different graphs on the same axis.

Step 2: Change the axis and modify the chart

• Select the 2^nd feature SUM(Profit) and choose the dual axis.
• In the marks card, change the shape of the SUM(Profit) (2) to circle.
• Add 'mark labels' in the 1^st SUM(Profit) from the Label card in the marks section; it will write the profit of each category.
• Adjust the size of the bar and the circle to give it a shape like a lollipop.
• Change the colour of the chart to make it more interactive.

This is what the bullet chart looks like:

Waterfall Chart

The cumulative effect of sequentially introduced positive and negative values is commonly shown using a waterfall chart, which is a graphical representation of data. Users can better understand how individual contributions-both positive and negative-add up to a total by using this kind of chart, which is particularly useful for visualising the impact of various factors on an initial value. Waterfall charts are an invaluable tool for anyone seeking to gain deeper insights into their data, as they offer a clear and intuitive means of analysing complex data sets.

The process to create a Waterfall Chart

First, add the Sub-Category to the Rows section and the Sales Measure to the Column area. A bar graph is what it will produce.

Using the Sort option in the subcategory and selecting Field under the Sort by option, step two involves sorting the bar graph in descending order.

Step 3: Incorporate Quick Table Calculation and choose the running total option in the row section.

Next, Select the Gantt Bars located on the Marks card in step four.

Fifth, change the chart's size. The sales measure can now be modified by dragging it to the marks card and adding a (-) sign. It will be -SUM([Sales]).

Step 7: Change the colour to make it more interactive.

The resultant graph will look like a waterfall falling from upwards to downwards direction. Here is the resultant graph:

Conclusion

Tableau is a robust tool for data visualisation that offers a multitude of chart types and customisation choices to its users. This tool makes it simple for users to design and modify visualisations to suit their needs. Tableau's flexibility enables users to analyse and present data in a way that is interesting and meaningful. Users are able to create visually appealing and informative data presentations that effectively communicate their message thanks to the wide range of chart types and customisation options available.