(Tableau Visual Analytics-TIPS & TRICK )

(Tableau Visual Analytics)

 

 1-TreeMap:

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1-Use treemaps to display data in nested rectangles. You use dimensions to define the structure of the treemap, and measures to define the size or color of the individual rectangles.

2-Treemaps are a relatively simple data visualization that can provide insight in a visually attractive format

3-: A slight disadvantage of using treemaps in Tableau is that, as the number of items increases, the amount of space allocated for each item decreases. Hence, the area available to print the labels becomes small. As a result, usually, in a treemap, 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 treemap

 

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2-         Build a Scatter Plot:

                 I.        Use scatter plots to visualize relationships between numerical variables.

                                   II.          When you have paired numerical data.

                                 III.          When your dependent variable may have multiple values for each value of your independent variable.

                                IV.          When trying to determine whether the two variables are related, such as: When trying to identify potential root causes of problems

                                  V.          A scatter chart works best when comparing large numbers of data points without regard to time. This is a very powerful type of chart and good when your are trying to show the relationship between two  variables (x and y axis), for example a person's weight and height.

3- Correlation:

With scatter plots we often talk about how the variables relate to each other. This is called correlation. There are three types of correlation: positive, negative, and none (no correlation).

• Positive Correlation: as one variable increases so does the other. Height and shoe size are an example; as one's height increases so does the shoe size.
• Negative Correlation: as one variable increases, the other decreases. Time spent studying and time spent on video games are negatively correlated; as your time studying increases, time spent on video games decreases.
• No Correlation: there is no apparent relationship between the variables. Video game scores and shoe size appear to have no correlation; as one increases, the other one is not affected.

4-How to Examine a Scatterplot:

Ø As in any graph of data, look for the overall pattern and for striking departures from that pattern.
Ø The overall pattern of a scatterplot can be described by the direction, form, and strength of the relationship.
Ø An important kind of departure is an outlier, an individual value that falls outside the overall pattern of the relationship