Tableau plays a very crucial role in data intelligence, data representations, data visualizations, and data modelling. The time has gone when folks used to draw graph, charts, on excel and variant types of resources or tool. Because provide us live data source accessibility with number of data sources like – spark, Google Products, Social network, programming language (R,Python,JAVA) whereas tableau uses VIZQL in background to speed up the performance. So now the time is to move towards Business Intelligence.As of now, you don’t need to worry about either data or data sources.
Are you planning to pursue a Tableau training course in Delhi? Then you must be well aware of this common confusion about the difference between these two widely used maps. There are two very useful charts which help in analyzing data, heat maps and tree maps. Heat maps and tree maps are highly insightful visualizations. However, many a times, there is a confusion between the two due to which analysts either use misuse it or totally avoid using it.
This article will help to draw a clear line between heat maps and tree maps, thus enabling analysts pursuing tableau certification, Gurgaon to create better visualizations.
We the faculty at Dexlab Analytics, the premiere Tableau Training Institute in Gurgaon aim to clarify this common doubt with this brief discussion on these two maps.
What are heat maps?
Heat map is a type of visualization tool that is very apt to compare different categories. It helps to visualize measures against dimensions with the help of colors and size to compare one or more dimensions & up to two measures. The layout is similar to a text table with variations in values encoded as colors. In heat map, you can quickly see a wide array of information.
In a heat map, one measure can be assigned to the color and another measure can be assigned to the size.
Quick Hands-On: Shows the sales and profit in all regions for different products category and sub-Category.
Analysis of visualization: The profit is represented by the color and ranges from red for loss to green for profit. The total sales are represented by the size.
Hence, it is very easy to understand the performance of different products in different regions, at one glance, just by looking at the heat map.
What are tree maps?
Tree maps are a relatively new feature in Tableau, first appearing in version 8.0. The ‘tree map’ is a chart type that displays hierarchical or part-to-whole relationships via rectangles. In case of hierarchical (tree-structured) data these rectangles are nested. The space in the view is divided into rectangles that are sized and ordered by a measure. Nested rectangles mean that hierarchy levels in the data are expressed by larger rectangles (above in the hierarchy) containing smaller ones (below in the hierarchy). The rectangles in the tree map range in size from the top left corner of the chart to the bottom right corner, with the largest rectangle positioned in the top left corner and the smallest rectangle in the bottom right corner.
In a tree map 1 or more dimensions & up to 2 measures are used to create such a map.
Quick Hands- On: Show the sales and profit in all regions for different products category and Sub-Category.
Analysis of the visualization: The profit (color) and sales (size) of products are given at a Category and Sub- Category level. Bigger the size of the node, greater is the sales in that state. Similarly, the greener the node, more is the profit in that state.
Summary: A slight disadvantage of using tree maps in Tableau is that, as the number of items increase, the amount of space allocated for each item decreases. Hence, the area available to print the labels, become small. As a result, usually, in a tree map almost all the squares or nodes will appear blank. This defect can be overcome by providing appropriate tooltips for each node. Like in heat maps, measures can be assigned to give different colors and sizes to the nodes in the tree map.
To learn the right use of these two maps in Tableau we recommend seeking a corporate Tableau Training in Delhi NCR for better understanding of this complex statistical application.
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