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Empty or missing data. Null is not equal to 0. For example if I have a dataset that is a list of purchase events, I might have a field called "price." If this field is missing from some events I would say that the value of price in those events is "null." In this example a price of 0 might mean "free," while a null might mean "I don't know" or "N/A."

Interana works well with data that has lots of null. It is common to use Interana with datasets that have thousands of fields, most of which are null in most events. This often happens when data is loaded from many sources into the same table in Interana. For example, a purchase event might have a price, while a photo upload event has a photo name, and a sensor reading has a color temperature in degrees C. These will all be null in the other kinds of events (purchase price probably doesn't record color data), but Interana can handle the null values.

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