Append Queries in Power Query: Combine Files Easily
Appending stacks tables with the same shape: a January table and a February table become one. Column matching and failure modes.
ETL and data preparation in Power BI.
13 tutorials in this category
Power Query is the part of Power BI that runs before any DAX does: connecting to a source, fixing the column types, unpivoting the month columns, merging in the lookup table. Every click in the editor writes M code, and that code is what actually executes — on refresh, against the source, possibly on a schedule you are not watching.
The sensible reading order is the getting-started walkthrough, then the transformations you will use every week (group by, unpivot, merge, append, conditional columns), then the M language underneath. Query folding belongs early too, even for beginners: folding is the difference between a refresh that takes four seconds and one that takes forty minutes, and a single step in the wrong place can break it without any error message appearing.
What this section deliberately avoids is doing work in Power Query that belongs in the model, or vice versa. Cleaning that never changes should happen upstream and be forgotten; logic that changes with every report belongs in a measure. Most slow models we look at are a case of that boundary being crossed in both directions at once.
Appending stacks tables with the same shape: a January table and a February table become one. Column matching and failure modes.
Merging queries in Power Query is the closest thing Excel users get to a familiar friend: VLOOKUP.
Excel remains the most common starting point for Power BI projects.
Excel assembles and argues over the data; Power BI models and distributes it. How the two hand off without duplicating work.
Folding turns editor steps into one query the source runs itself. Why a single step can silently break it, and how to check.
Month-by-column reports become a tidy long table in three clicks. The exact steps, the column to keep fixed, and the usual pitfall.
Summarise rows by category: count, sum, average, min, max. Multiple columns, the M code it produces, and why totals come out wrong.
Add a new column with an if statement in Power Query, without writing M. The dialog, nested conditions, generated code, and bucketing patterns.
Ten Power Query steps that handle the messy exports analysts actually get: inconsistent names, merged headers, malformed dates.
Swap environments, date ranges or test data from a dropdown instead of editing M code. How to create parameters and pass them in.
Merge is a join that adds columns. Append is a union that stacks rows. The difference, the join types, and which one costs more to refresh.
M is functional, not a spreadsheet formula. Its three core data structures, how functions compose, and why the editor stops being scary.
Connect, transform and shape data with the no-code editor, plus a look at the M code it writes behind every click.