Question

How to handle column type inconsistencies in Power BI transformations?
During data import or integration from multiple sources, columns may have inconsistent data types (e.g., numbers stored as text or mixed date formats). This question explores the challenges caused by such inconsistencies—like failed transformations, inaccurate aggregations, or disabled query folding—and outlines strategies to enforce data type integrity using Power Query, including conditional type detection, schema alignment, and robust type conversion techniques.

Answer 1

In Power BI, managing column-type inconsistencies is essential to guaranteeing precise data analysis, clear model relationships, and optimal performance throughout transformations. When data comes from different sources (such as Excel, SQL Server, and Web APIs) and column types are not consistently defined, these inconsistencies usually arise.

Here's how to properly handle Power Query column type inconsistencies:

1. Clearly Establish Data Types Earlier

After loading the data or after any transformation step that could alter the types (such as merging or appending), always set the column data types right away.

To manually set each column, use the Transform > Data Type dropdown.

Or use a Table in the Advanced Editor.ChangeColumnTypes. 

2. Use Conditional Type Detection

If data type varies across rows (e.g., some numbers stored as text), use conditional logic to standardize it.

Table.TransformColumns(Source, {
  {"Amount", each try Number.FromText(_) otherwise null, type number}
})

This ensures that invalid entries are either corrected or marked as null for further cleaning.

3. Handle Mixed Types Using try...otherwise

Wrap conversions in try...otherwise to avoid errors during type casting.

Table.AddColumn(Source, "CleanedAmount", each try Number.From([Amount]) otherwise null)

This helps gracefully handle rows where data type conversion would otherwise fail.

4. Prior to adding queries, use schema alignment.

Make sure the data types and column names match when appending tables from various sources.

Utilize the Table.PromoteHeaders, then Table. To align the schema, transform column types.

Make a template table with the appropriate format if needed, then add more to it.

5. Turn off Auto Type Detection (Power Users can choose to do this).

Column types may be inferred incorrectly by Power BI's auto-detection during load. Under Options > Data Load > Auto detect column types and headers for unstructured sources, you can turn off this feature.

6. Use Profiling Tools to Verify

Before loading the model, use Power Query's Column Quality and Column Distribution to check for data consistency, find mixed types, and spot possible problems.

7. Awareness of Query Folding

Incorrect or inconsistent column types may break query folding.