After teaching the Advanced SQL Masterclass recently, one of the attendees confronted me with an interesting challenge for me to solve with all the tools I had been discussing all day. This challenge originates in the world of insurance and revolves around policies. Apparently (I am not much of an insurance expert) policies can have periods of inclusions (when they are valid) as well as periods of exclusion (when the policy is definitely not valid, even when there are inclusions that suggest the opposite. The exclusions win, so to say.

Visually, I can describe the situation for one specific policy like this:

Here we see a policy with five inclusions (in green), that partly overlap, as well as four exclusions (in red). The challenge is that we need to find out from a table that contains all periods of inclusion (green) and exclusion (red) what the resulting periods of validity are for the policy. Visually that would be deriving the blue bars in the following figure:

This article describes how this challenge can be approached in SQL.

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