A data analyst is working on a sales report that includes a slicer for 'Store_Region'. The analyst selects 'North' from the slicer and notices that sales data from a major city known to be in that region are missing from the report's visuals. However, data from other cities in the 'North' region are displayed correctly. The slicers for 'South' and 'West' regions appear to work as expected. Which of the following is the MOST likely cause of this issue?
The report is experiencing a slow refresh rate.
The report has an excessive load time.
The 'Store_Region' column in the source data contains inconsistent values, such as leading spaces or alternate spellings.
An incorrect join type is being used in the report's underlying data model.
The correct answer is that the 'Store_Region' column contains inconsistent values. This is a common data quality issue where variations like ' North' (with a leading space), 'N. Region', or misspellings prevent the filter from correctly grouping all intended records. When the analyst selects 'North', the slicer only includes rows with that exact value, excluding the variations. The other options are less likely. A slow refresh rate would affect the timeliness of the data, not the logical behavior of a filter on existing data. Excessive load time is a performance issue, not a data accuracy issue related to filtering logic. An incorrect join type would likely cause more widespread issues, such as missing data for all regions or incorrect totals, rather than affecting only a subset of records for a single filter value.
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