Businesses that predominantly monitor customer behaviors and virtually pinpoint certain locations when tracing mobility, no doubt, have a large amount of data at hand. With this, analyzing and providing an interpretation regarding your data is one of the greatest challenges for companies since several
Businesses that predominantly monitor customer behaviors and virtually pinpoint certain locations when tracing mobility, no doubt, have a large amount of data at hand. With this, analyzing and providing an interpretation regarding your data is one of the greatest challenges for companies since several figures are not primarily organized or grouped which will also take a great deal of time. It would then be much easier for businesses to utilize a tool that essentially help understand trends and answer spatial questions with the use of charts or maps.
Through a software which allows data visualization such as Tableau, maximize your current geographical data by creating effective lay-outs that respond to questions regarding areas and locations. Maps are one of Tableau’s most efficient chart types for they immediately assist decoding of latitude and longitude combinations which enable you to recognize patterns among placements that might be initially difficult to identify. In addition, population based in census, revenue, and other common demographic data are included as well.
Find out which map is the most suitable for your data.
Types of Maps in Tableau
1. Proportional symbol maps
Proportional symbol maps are fit when demonstrating one or two quantitative values for particular areas where one value can be encoded through size and another encoded in color, if needed. By way of illustration, earthquakes around the world occurring between specific dates can be plotted through sizes according to magnitude as well as with the use of color for further visual detail. Also, providing descriptions which explains what the size represents will be helpful and will prevent misinterpretations.
2. Choropleth maps (filled maps)
Excellent for displaying ratio data, choropleth maps or filled maps are extremely useful if you want to see spatial trends. Only one value for every polygon is shown on an average choropleth map while a bivariate choropleth map illustrates two distinct but associated values that are color coded. This makes it easier to assess two characteristics in connection to one another. With interactivity added to the legend, visually interpreting the data becomes easier in which this type of map can be partitioned to single groups or a whole category.
3. Point distribution maps
When one intends to demonstrate estimated locations and how these are distributed in a cluster for visual data, a point distribution map can be utilized. In order to create this type of map, the latitude and longitude coordinates of the locations are needed.
4. Heat maps (density maps)
Create a map that displays patterns or comparative levels, which could not be seen at first due to overlapping marks, through heat maps or known as density maps. Tableau helps illustrate heat maps by grouping and coding overlay marks based on the group’s number of marks. Likewise, heat maps are greatly efficient when using a set of numerous data points in a narrow geographical area.
5. Flow maps (path maps)
Flow maps allows you to connect routes or paths and let you observe where things have gone over time. Not only that, flow maps are also useful when one wants to see spatial patterns due to location changes or connectivity exploration between areas. When generating a flow map, your source of information should include the latitude and longitude coordinates of each data point in a route, a column to set the order for the points to be connected, a distinct ID for each route, and necessary data points for shaping each route into a row.
6. Spider maps (origin-destination maps)
A spider map is used to demonstrate how a place of origin and one or more areas of destination interact. For instance, paths between metro stations can be connected as it is being plotted on the map or follow rides for bicycle sharing from one place to multiple locations since spider maps are pleasant to work with routes connecting to several points nearby.
Let your data tell its story through 