Question

How do you handle data type mismatches or conversion errors in Power Query when merging or appending tables?

I'm working on a project that involves merging and appending multiple tables in Power BI using Power Query. During this process, I've encountered data type mismatches and conversion errors that are causing issues with the data load and transformation. For instance, some columns expected to contain numeric values have text entries, or date formats are inconsistent across tables, leading to errors or unexpected results.

Are there specific techniques or best practices to handle data type mismatches and conversion errors in Power Query to ensure smooth merging and appending of tables? Any guidance on tools or steps to address these data inconsistencies would be greatly appreciated!

Answer 1

When merging or appending tables in Power Query, it is important to take care of data types and conversion errors. Here are key techniques and best practices:

1. Data Type Consistency:

Check Data Types: Before merging the tables, ensure that the respective columns have the same data types throughout all the merged tables. Use the "Change Type" command to apply the desired data type.

2. Change Apex Data Type

Replace Errors: For errors caused by type mismatches, the "Replace Errors" function can change that particular type of error to a generic one or even to a null value.

Conditional Columns: make conditional columns to accommodate the differences in formats, especially when text is to be translated to numbers, among others.

3. The 'Try' Function

Implement try: This is the other method of trying to convert data, but it allows for some level of failure. For instance, do not trust Numbers.FromText([YourColumnName]), use try instead when trying to change text that has numeric information to numeric form.

4. Dates Should be in the Same Format

Unify Dates: All the date columns in the different tables under the same heading should be in the same format. Use calculated columns to extract and standardize the formats of dates within set baselines.

5. F Final Checks

Query Review: Before uploading data in BI or Power BI, it is advisable to check if all the columns are in the appropriate data type. B. Data Profiling: Use data profiling management functionalities to process and identify data type issues before performing changes.

Adapting these processes will make it easy for you to handle data type discrepancies that often occur when merging or appending tables in Power BI.

Answer 2

Here are the best practices to follow when working with data type mismatches and conversion errors in Power Query during the merging of tables or appending tables:

Standardize Data Types: Before merging or appending tables, ensure all tables have consistent data types for each column. Explicitly define the data types for each column in the "Transform" tab, such as "Text," "Number," or "Date." If types don't match, resolve by converting incorrect entries (for example, replacing text values with nulls, where a numeric value is expected) using either "Replace Errors" or "Replace Values."

Clean and validate the data: Clear errors in data using "Remove Errors" or "Replace Errors" or by specifications with conditional custom columns. For dates, standardize the formats using "Transform > Data Type > Date" and splitting-recomposing this column where necessary, which will also resolve the non-conformance.

Error handling steps: Use functions such as Table to include an "Error Indicator" column. Add a column to capture the rows causing trouble. Preview transformations to catch issues before saving. Ensure appends match exactly in headers since this may cause hidden errors due to a name mismatch.

Standardizing your data and using these error-handling tools prevents interruptions in your workflow in Power Query.