Power Query - Beginner to PRO Masterclass in 30 minutes: Excel learning resource
Power Query - Beginner to PRO Masterclass in 30 minutes
A tighter 30-minute tour built around one realistic staff dataset instead of several separate examples.
What this video actually covers
A tighter 30-minute tour built around one realistic staff dataset instead of several separate examples. After a short web-scraping example to show Power Query pulling data from outside Excel, most of the video works through cleaning a genuinely messy staff table: fixing date formats, splitting a combined name column into first and last name, bucketing a numeric salary column into ranges, and calculating each employee's tenure from their start date. The last few minutes go further than a typical beginner video by writing a small piece of M code by hand instead of using the point-and-click editor, for a transformation the UI can't easily do.
Where to jump in
What to practice while watching
- Load the messy-data practice file into Power Query and fix its date-formatted column the way the video fixes dates in the staff-data section.
- Split a combined name column into first and last name using the Split Column tool.
- Bucket a numeric column (for example amount or quantity) into ranges the way the video buckets salaries into tiers.
- Try writing one small M code step by hand instead of using a menu command, following the video's closing example.
Exercise file
Practice the steps above on a real workbook instead of a blank sheet — no sign-up required.
Download Messy data cleanup practice (.xlsx)Recommended learning path
Start by watching the lesson once without pausing, then reopen Excel and rebuild the example with your own small dataset. Save one clean practice workbook before moving to the next topic.
Source details
- Channel: Chandoo
- Format: video
- Level: Mixed
- Topic: Data Cleaning
Go deeper with this skill
Turn messy imported data into a reliable table that formulas, pivots, and reports can use safely. For this article, the goal is to practice: A tighter 30-minute tour built around one realistic staff dataset instead of several separate examples.
Practice workbook setup
Copy messy sample data to a raw-data sheet and keep the original untouched while you clean a separate working copy.
Practice workflow
- Identify the expected columns and data types before changing anything.
- Remove obvious blanks and duplicates, then check whether any removals need business approval.
- Standardize spacing, casing, dates, and number formats.
- Create a small before-and-after table so the cleanup can be reviewed.
Quality checks
- The row count before and after cleanup is explainable.
- Key columns have no unexpected blanks.
- Dates, IDs, and amounts are stored as the correct data type.
Common mistakes
- Cleaning directly over the only copy of the data.
- Removing duplicates without deciding which columns define a duplicate.
- Fixing visible rows while hidden filtered rows stay messy.
Next actions
- Convert the cleaned range into an Excel Table.
- Repeat the same cleanup with Power Query if the data will arrive again.
Formula focus: even if this workflow is not formula-heavy, add one check cell that confirms the final output still matches the source data.
