This week's tip explains two concepts for drilling down into your data: marking and filtering.
Marking is the ability to visually highlight records of interest very easily. The effects of marking are not just to visually highlight data on the page, it is also so that we can apply further analytics to that marked data, whether it is applying statistics to it, exporting it, displaying it in another visualization, or a variety of other capabilities. In this tip we will look at using marking to create details visualizations.
In the example below, we show sales data from stores in four locations: Boston, Los Angeles, New York, and Seattle. Suppose we want to drill-down into the data and only look at sales from the Los Angeles stores?
For this, we can setup a details visualization, which will only show data that is marked in another parent visualization.
Assume the Bar Chart below is the parent visualization:
If we want the details visualization to be a Line Chart, only showing data marked in the Bar Chart, we can right click in the Bar Chart and select 'Create Details Visualization > Line Chart'.
This will create a new Line Chart that appears just like any other Visualization. We can configure it just like any visualization also. However, there will be no data loaded in it by default.
Since this is a details visualization, we only see data when records are marked in the Bar Chart.
With Spotfire, you can also define multiple markings, so you can create a series of unique markings, each their own details visualization(s), which can also span across multiple pages. We will see an example of this later on.
We can also combine marking with filtering. Filtering allows us to filter out records based off certain criteria using the Filter Panel.
Suppose we only want to look at one specific age group in our analysis? Let's say, for example, we now want to only show customers in Los Angeles who are in our target age group of 45-60. We can then update the 'Customer age' filter in the Filter panel to only show records between 45 and 60 using the slider.
This will now update all our Visualizations to only show records where the customer age is between 45-60. Combine this with the criteria we already used to drill-down into Los Angeles stores only, we are able to see and analyze a specific cross-section of our customers.
Want to see what happens when you put this all together? View our latest Analytics in Action file where we walk using through a Spotfire analysis to help the store answer two analytical questions: Which 50 customers should they target for a marketing campaign, and which single customer should they select as a new spokesperson. You will see marking and filtering, combined with some other Spotfire techniques like bookmarks, used to create a Spotfire analytical file. Also note that use of multiple markings, each with their own sets of details visualizations'try doing this in Excel.
