Visualizing data using the Maps feature in Oracle Analytics is very compelling to any audience. It really speaks to our sense of "where" the action is happening, which is basic when it comes to information gathering or problem-solving. Let's look at how adding a map layer to a column in a data visualization gives the most rapid and relevant answer to the "where" question in a data story.
Maps leverage the geographical concepts we have been exposed to from a very young age. It provides an enormous (almost unfair) advantage vs. other data visualizations since it requires less brain power to understand the visualization and enables more focus on insights revealed by the data.
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Let's take a simple example of analyzing sales by country. How long does it take to understand the first data visualization you see below versus the second data visualization?
1) Bar chart depicting sales by country
2) Map depicting sales by country
So, which of these visualizations was faster for you to comprehend?
By default, most data visualization tools will default a dimension plus a metric into a bar chart or a variant of a bar chart. But when it comes to geographical objects, these are a lot easier to visualize on a map rather than a bar chart. Oracle Analytics allows you to easily assign a behavior for a given column to visualize it directly on a map by default. It also allows you to specify which map layer it should default with.
The option exists to manually assign a map layer to a column in a dataset. As you can see in the screenshot below, you go to the Prepare tab, choose the column you want to assign a map layer to, right-click, and from there you can choose Location Matches.
Choosing the Location Details option will open the Location Match dialog box, which shows the suggested best-matched map layer and quantitative information as to how well the data is matched with the map layer's data.
You have the option to choose any map layer from the existing catalog and assign it to that data column by clicking on the OK button. The system will not let you choose a map layer that does not match with any of the data; the option, in this case, is disabled:
After a successful assignment, you will notice a Location icon on the column which has a map layer assignment.
There are three significant advantages to assigning your columns to map layers:
1) There are clear visual indications on columns that have been assigned a map layer.
Imagine you have a dataset with many columns. There might be some columns that can match a map layer, but it is very difficult to find them. The names of the columns might have changed, or it might not be evident that a map visualization is relevant to a particular column, or you might not even know that a specific map layer exists for a column. In these cases, you might be using a different visualization to discover insights, which can be tedious and time-consuming. With these map layer indicators, columns to be visualized can be easily identified.
2) It is easy to change the default behavior to directly default to a map visualization when using assigned columns.
Previously, we discussed how a bar chart and other variants were suggested as the best visualizations when columns such as city, state, country were being used. Now with the assignment of a map layer to a column, the best-suggested visualization will be the map visualization. If you have multiple columns, each having map layers assigned, the map visualization will be suggested and all the columns with map layer assignments will be on the Location edge of the map visualization.
3) Time taken for the map to render is reduced.
The process of finding the “best fit” map layer from the existing catalog of map layers can be a time-consuming operation. But with the Oracle Analytics Maps feature, you can manually assign a map layer to a column, by-passing this entire process and rendering the map along with map layers much faster.
You can see the entire process in action in this video:
Finally, it is easy for the user to directly override data visualization behavior when building a data visualization. You can choose to represent a column with visualizations other than maps, or with other layers. But the default behavior is designed to take you to a friendly place with easy to use tools for showing and visualizing data.