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This article only applies to movement data

This article is only relevant when working with movement data, not when working with time series data.

You can read more about the differences between the two in this article.

Different strategies to deal with missing data values

Some datasets contain records where one or more values are missing.

The platform has 2 strategies to deal with those missing values:

  • Leave the value missing: the record will be processed with the missing value (except when the missing value is a required property like for example the timestamp). This is the default behavior.

  • Copy the missing value from a previous record: the platform will try to find an earlier record with the same id where that value is available, and copy that value.

Illustration of how the missing value remains missing or is copied from an earlier record
Figure 1. Illustration of both strategies

How to configure it ?

When you are creating or editing a data set, click the Configure Processing Settings button:

The top navigation bar with the Configure processing settings button clicked
Figure 2. The Configure processing settings button in the top navigation bar when creating/editing a data set

On this page, you can select which strategy to use.

You can always adjust the strategy

even when data has already been processed.

The only caveat is that adjusting the strategy requires the data set to be processed again. This takes some time.