Tableau Basics

Overview

Time: min

Objectives

• Introduction to Data Types, and Types of Charts in Tableau.

Data Types in Tableau

• All the variables in the dataset have a data type. It tells us the kind of information stored in that field. Tableau has specific data type icons which tell you about the data type.

Sometimes, tableau might interpret the data type wrong. For example, it might consider the date type as integers as it has numbers in it. You can always change the data type of the field.

• There are several methods to do so. The easiest is to go on the data type icon and click. You will see a list of data types. Select the one you want and it will be changed.

• Choosing the right chart type This is one of the most important skill to have while dealing with data visualization. The points that you need to consider while making a visualization are what questions you are answering and what insights you are getting. With experience you will be able to assess what chart type you want to create. Here are some examples –

• a. Magnitude Charts – It shows the relative size/value of two or more discrete items. For example, if you are comparing sales of different regions you want to compare the magnitudes. They include bar charts, line charts, packed bubble chart.
• b. Ranking Charts – Sometimes you want to depict the relative ranking of all the members of your dimension. For example, showing the top 10 sales people. Ranking charts include bar graphs with rank calculations.
• c. Distribution Charts – They are helpful in plotting the frequency of an event within a population. For example, frequency of incoming calls by day. Distribution charts include histograms, population pyramids and box plots.
• d. Deviation Charts – Deviation charts show how the values deviate from a baseline value. That baseline value could be the average or the median. For example, if an item has unusually high or low profits you use deviation charts. They include bullet charts, bar charts and combination charts.
• e. Change over time Charts- To observe change in a variable over time we use these visualization. The charts include line charts, slope charts, highlight tables.
• f. Part-to-Whole Charts – To observe how much of a whole an individual part takes up you need part-to-whole charts. For example, how much a region contributes to overall sales. The charts may be pie charts, area charts, treemaps and stacked bar charts.
• g. Spatial Charts – These are the charts that display the precise locations and geographical patterns in your data. For example, map of all sales across the country. They include filled maps, point distribution maps, symbol maps and density maps.
• h. Flow Charts – They include path over time and path between origin and destination charts. For example, identifying the longest shipping route.

Key Points