Excel & Automation
Preparing data with Power Query
Build a repeatable preparation process with appropriate sources, explicit data types and quality checks.
Published:
2 min read
This article provides general technical guidance for learning purposes. It is not a customer project or case study.
Define the source and scope
Power Query can connect to data and define transformation steps in Excel or Power BI. Importing a file is only the beginning; the goal is to apply the same rules on later refreshes. Establish the source structure, required columns and records the report should cover.
In an illustrative training scenario, monthly sales files arrive with different column names and date formats. These differences need to be normalised before analysis. The scenario is not a customer case study.
Make data types and quality explicit
Select date, decimal and text types deliberately, paying attention to locale-dependent dates and decimal separators. Define business rules for missing values, conversion errors and duplicates. Investigate errors instead of silently dropping rows, and track which records are excluded.
Give queries and transformation steps descriptive names. Check key uniqueness before merging tables: unexpected multiple matches can change totals. Reconcile output row counts and important amounts against the source.
Design for refresh from the start
Removing unnecessary columns and out-of-scope rows early limits the data processed later. With supported sources, query folding can delegate suitable transformations to the source; it does not apply to every connector or step. Review refresh credentials, file locations and gateway requirements where relevant. Documented steps that do not depend on manual file corrections support a more sustainable preparation process.