Many customers ask us why " " and "(empty)" are displayed in the Power BI Slicer. What does this mean?
In the world of Power BI and other data analytics tools such as Microsoft Dynamics NAV (Navision) and Business Central, null values and empty values are common terms that are often confused. However, it is important to understand the difference between these two concepts as they can have different meanings and implications for your data analysis.
Zero values
A zero value (NULL) in a database represents the absence of a value. It means that no data is available. Null values are particularly useful to indicate missing information. In the database world, and especially in systems such as Microsoft Dynamics NAV or Business Central, null values can be interpreted in different ways:
- Unknown valueThe value has not yet been entered or is not currently known.
- Not applicableThe value is not relevant for the given context.
In Power BI, null values are often displayed as "empty" or "null". If you use a slicer that contains a column with null values, these null values are displayed as "empty" to show that no information is available for these records.
Empty values
An empty value, on the other hand, is a value that is explicitly saved as empty or without content. This can be an empty string (""). In Microsoft Dynamics NAV and Business Central as well as in other systems, empty values can mean that the user has deliberately decided not to enter a value, even if the information is known or would be applicable.
In contrast to null values, which indicate the absence of a value, empty values signal a deliberate entry of "nothing". In Power BI slicers, these empty values often appear as "" or " ", which visually shows that an empty string has been saved.
Differences in data analysis
Distinguishing between null values and empty values is critical to correctly interpreting and analyzing your data. Here are some examples of how these differences can affect your data analysis:
Filter and slicer:
- In a Power BI slicer, both null values and empty values can be displayed, but with different meanings. Null values appear as "empty", while empty strings appear as
""or " " are displayed. - When filtering or slicing data, it is important to know which values are missing and which are intentionally empty in order to create accurate analyses.
- In a Power BI slicer, both null values and empty values can be displayed, but with different meanings. Null values appear as "empty", while empty strings appear as
Aggregation and calculations:
- When aggregating data, zero values can lead to different results than empty values. A null value is often ignored, while an empty value is taken into account as an actual (albeit empty) data point.
- In Microsoft Dynamics NAV and Business Central, this can be particularly important when creating reports and dashboards.
Data integrity and cleansing:
- When you clean data, you must decide whether you want to replace null values or retain empty values. This decision can affect the integrity and accuracy of your data.
Conclusion
Understanding the differences between null values and empty values is critical to the effective use of Power BI, Microsoft Dynamics NAV (Navision) and Business Central. While null values indicate the absence of a value, empty values signal a conscious decision not to enter content. Both have different effects on your data analysis and should be handled accordingly.
By interpreting and handling these values correctly, you can ensure that your data analysis is accurate and meaningful, which ultimately leads to better business decisions.
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