Error handling
Implementing error-handling strategies extends beyond addressing raised errors alone. It is as much about making choices and using techniques available in the M language to effectively mitigate errors and ensure the robustness of your data transformation workflows. When working with data, it’s common to encounter errors such as missing values, incompatible data types, and unexpected or invalid calculations. To address these challenges, every technique should be considered. The aim is to implement error-handling strategies that will help avoid, manage, and resolve errors right where they occur, ensuring a predictable outcome as a result. Here’s what is in your toolkit:
- Coalesce, dealing with nulls
Power Query’s M language supports null propagation, which means that if a value is
null
in a sequence of operations, the result will be null. Thea
field inmyRecord
illustrates this. It is this behavior that helps to prevent errors that...