Power Query Tutorial

What this does

Power Query — shown in the ribbon as Get & Transform — is the import-and-clean layer that sits in front of the worksheet. Its defining property is that it RECORDS every step rather than performing it: removing a column, splitting one, changing a type, filtering rows and unpivoting all land as an ordered list in the Applied Steps pane. Point it at next month's file and click Refresh, and the whole sequence replays. That makes it the correct answer to any cleaning job you will do more than once, and to combining a folder of identically shaped files (Get Data ▸ From File ▸ From Folder). Two operations have no practical worksheet equivalent: Unpivot Columns, which turns a wide twelve-month-columns layout into the tall three-column shape every PivotTable wants, and Merge Queries, a join that handles many-to-many where VLOOKUP cannot. It is built into Excel for Windows from 2016 and into Excel for Mac from 2019, though the Mac version supports fewer connectors. The same idea underpins a lot of everyday Excel work, so the few minutes spent getting it right here pay back across every sheet you build afterwards. Treat it as a pattern, not a one-off, and it stops being something you look up and starts being something you reach for. The difference between a quick fix and a sheet you can trust is the extra minute you spend validating “power query tutorial”. Start on a copy or a tiny sample, keep the affected cells visible, and compare the result with the tool above before you touch the real workbook. When this is a ribbon command, the selection matters more than the button: confirm the range, apply the command, then spot-check the output before saving. The point is a data step that keeps your analysis trustworthy, but the practical win is that someone else can open the file and understand what happened without asking you.

A worked example

Twelve monthly CSV exports in one folder, each with the same headers. Data ▸ Get Data ▸ From File ▸ From Folder ▸ pick the folder ▸ Combine & Transform. Power Query stacks all twelve, and the steps you then add — remove a blank column, set Date to date type, filter out cancelled rows — apply to every file. Next month, drop file thirteen into the folder and press Data ▸ Refresh All. Any cleaning routine you perform more than once is a query you should have built the first time — the second month costs one click instead of an afternoon. One habit worth forming early: name the cells that hold your inputs, so the formula reads in plain language instead of a string of cell addresses. A reviewer — or you in three months — can then follow the logic without decoding what B7 and D2 were supposed to mean, which is most of what makes a sheet maintainable.

In Google Sheets

If you are in Google Sheets rather than Excel, the good news is that the formula shown here is identical and the workflow barely changes — menus sit across the top instead of in a ribbon, and a few function names differ slightly, but anything you build here moves across with little or no rework. The aim was to get you unstuck fast and leave you a little more capable than a copy-paste would. The answer is at the top, the tool proves it, and the detail above shows why it holds — so the next time a colleague asks, you can answer without reaching for search. Treat “power query tutorial” as a small building block rather than a chore. Once the inputs sit in their own cells and the formula reads from them, the same setup answers a dozen related questions with a tweak, and Excel keeps every dependent figure current as the data changes. The tool above is there so you can rehearse and verify before committing anything to a real workbook; the steps and worked example are there so the logic sticks. Get it right once and it stops costing you time — it starts saving it, every time the question comes back around.

Common mistakes

• Editing the loaded output on the sheet — the next refresh overwrites it. All edits belong in the query.
• Skipping Change Type, so numbers arrive as text and every downstream total is wrong or zero.
• Filtering on a value list, which hard-codes today's values into the step and silently drops new ones later.
• Combining files whose headers differ slightly; the step records column names, so "Amount " with a trailing space breaks the append.
• Loading a million rows to a worksheet instead of Close & Load To ▸ Connection Only ▸ Add to Data Model.
• Building the same clean-up by hand each month when the query already exists and just needs Refresh.

Frequently asked questions