Key data analysis skills you should learn (Part 2)

The next types of analysis I'm going to focus on are Key Metrics and Ranking Analysis.

Key Metrics
Key metrics displays one key piece of information prominently (examples include total sales, total profit or total number of customers) and by using ratios you can get deeper insight and more information from your key metrics.  For example we could create key metrics for displaying the profit ratio (which is the total profit divided by total sales) where the  profit ratio is displayed as a percentage, this makes it easier to see what portion of your sales is profit.

Another ratio that can be calculated is the average sale per customer or the average profit per customer.  In this case you would divide the total sales by the number of customers and the total profit by the number of customers, so by using three key metrics you have now created three new key metrics using ratios which gives further insight into your data.

Ranking Analysis
Ranking analysis is about understanding the top/bottom values within a range.  The simplest form of ranking is to do a sort from highest to lowest or lowest to highest but there are many more rankings that can be done.

Top 10 or bottom 10 is one of the common method of analysis to highlight the items that are contributing the highest or lowest within your data set.  Filtering your items to only show the top 5, 10 or 20 makes it easier for you or your audience to view the most important items in a table, rather than displaying a long list of items.  A top 10 or bottom 10 analysis can also be combined with your column or bar graphs to restrict the number of items that are displayed in the graph.
You can also use a top/bottom percentage filter, in other words limiting the list of items to the top 20% or bottom 20% and this again easily allows your audience to focus in on the key values within the data set.