M Is for (Data) Monkey A Guide to the M Language in Excel Power Query

What it’s about

Written by Power Query experts Ken Puls and Miguel Escobar, 'M is for (Data) Monkey' liberates Excel pros from the soul-crushing cycle of manually importing, cleaning, and reshaping data every reporting period. Through carefully layered, hands-on chapters, the book shows how Power Query's intuitive interface can append files, merge tables, unpivot cross-tab data, import from folders, databases, the web, and Exchange, and then refresh the whole solution with a couple of clicks. For those willing to go deeper, it demystifies the M language—custom columns, functions, conditional logic, parameter tables, and dynamic calendars—so readers can build robust, reusable, and maintainable ETL solutions without mastering SQL or VBA. The result is a dramatic reduction in labor time, fewer copy-paste errors, and data solutions that outlive their creators.

The through-line

Who it’s for

An Excel professional or 'data monkey' who wants to spend less time cleaning and reshaping data and more time delivering valuable analysis.

The problem

Raw data arrives dirty, in many formats and files, and must be manually imported, cleaned, and combined before it can be used. They feel like undervalued grunt workers trapped in tedious, error-prone, repetitive labor.

The plan

1. Install or locate Power Query in your version of Excel and download the example files.
2. Learn to import, transform, and load data through the menu-driven interface following the ETL model.
3. Automate appending, merging, grouping, and unpivoting to eliminate manual copy-paste work.
4. Layer in M language techniques—custom functions, conditional logic, and parameter tables—for advanced, dynamic solutions.
5. Organize queries into staging and loading groups and automate refreshing for lasting, shareable solutions.

The payoff

Data import and cleanup that once took hours now completes with a couple of refresh clicks. · Solutions are reusable, maintainable by others, and survive with minimal training. · You add real business value by turning raw data into information quickly and accurately.

See our guide

• Practice Business Intelligence & Data Science →

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Additional reading

• Power Query Formula Categories (MSDN Documentation) · Microsoft

  The book explicitly points to this official Microsoft documentation as the comprehensive reference for all M language functions, which is essential for writing custom formulas and functions beyond the UI.

• PowerPivotPro.com (Rob Collie's blog) · Rob Collie et al.

  Mentioned in the acknowledgements and in the context of the Power Update tool, this resource is a key community hub for learning about Power Pivot and the broader Power BI stack, which are common destinations for data prepared with Power Query.

• Power Update (Third-party Add-in) · power-planner.com

  The book dedicates a section in Chapter 16 to this tool as a solution for advanced, automated refreshing scenarios that go beyond the built-in capabilities of Excel, especially for publishing to various destinations.

Featured in these guides

• Practice Business Intelligence & Data Science →Cited source