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M Is For (Data) Monkey: Power Query Guide - Non Fiction - Paperback

SKU VRT-2750

ISBN: 9781615470341

Publisher: Holy Macro
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Title:
M Is for (Data) Monkey

Condition: BRAND NEW
Format: Paperback

Overview:
M Is for (Data) Monkey is the definitive beginner-to-intermediate guide to the M language behind Power Query, the data-cleaning engine at the heart of Excel and Power BI. This practical handbook shows you how to transform messy, disparate data into clean, reliable inputs ready for dashboards, models, and analytics. Written for analysts, Excel professionals, and BI practitioners, it breaks complex concepts into approachable, hands-on steps. You’ll learn how to connect to diverse data sources, shape and merge data with confidence, and craft reusable queries that power repeatable reporting pipelines. The book blends clear explanations with real-world examples, guiding you from simple transformations to advanced M techniques that automate repetitive tasks and reduce manual data wrangling. Whether you’re building a KPI dashboard, preparing a data model for Power Pivot, or delivering self-service analytics across a team, this paperback edition delivers practical skills you can apply immediately, boosting accuracy, speed, and confidence in every data project. The result is a more efficient workflow and data you can trust for decision-making.

What Makes This Book Stand Out:
What sets M Is for (Data) Monkey apart is its laser focus on Power Query’s M language, with emphasis on tangible, repeatable results rather than abstract theory. The authors pair accessible prose with concrete, copy-ready examples that map directly to real business scenarios—from cleaning inconsistent date formats to harmonising columns across multiple sources. The step-by-step approach demystifies M code while still teaching readers to read and write M expressions, making complex data transformations feel approachable for busy professionals. The narrative bridges Excel’s familiar environment with the Power BI data model, showing how well-designed queries propagate through the entire analytics stack. For anyone aiming to speed up data preparation without sacrificing accuracy, this book becomes an indispensable practical reference.

Who This Book Is Perfect For:
If you’re an Excel user expanding into BI or a data professional seeking a reliable anchor for Power Query, this book is for you. It targets readers who want to master the M language, improve data-cleaning workflows, and deliver cleaner inputs for Power Pivot and Power BI models. It’s ideal for analysts, data engineers in training, and team leads looking to standardise data transformation across projects. Beginners will appreciate the clear onboarding, while intermediate readers will value the practical, code-backed techniques that scale across datasets. This title also makes a thoughtful gift for colleagues stepping into data analytics, or for students preparing for real-world data challenges.

Key Highlights:

  • Clear, hands-on guidance to the M language in Power Query
  • Step-by-step workflows that turn messy data into clean, usable inputs
  • Practical examples tied to Excel and Power BI data workflows
  • Reusable query patterns that accelerate daily data tasks
  • Bridges between Power Query, Power Pivot, and the data model
  • User-friendly explanations that empower self-service analytics
  • Real-world datasets that reflect common business scenarios
  • Concise, screenshot-supported instructions for quick learning

About the Author:
M Is for (Data) Monkey was co-authored by Ken Puls and Miguel Escobar, two respected figures in the Excel and Power BI communities. Ken Puls runs Excelguru Consulting and has been recognised as a Microsoft MVP for Excel, bringing industry-tested insight and practical, real-world experience to data transformation. Miguel Escobar complements the duo with deep Power Query expertise and a track record of helping professionals implement efficient data workflows. Their collaboration results in a approachable, results-driven guide that blends theory with hands-on technique, making the M language accessible to a broad audience while remaining valuable for seasoned practitioners. This authoritative pairing has established them as trusted voices in Power Query, and their book remains a popular reference for building robust data-cleaning pipelines.

Why You’ll Love This Book:
For anyone serious about data accuracy and speed, this book is a practical beacon. It doesn’t just teach syntax; it shows how to apply M to real-world data scenarios so your dashboards refresh reliably and your reports reflect trustworthy figures. The approachable tone, concrete examples, and emphasis on reusable patterns make it an essential daily reference for Power Query users—whether you’re tackling a one-off data-cleaning task or designing scalable data pipelines for an entire organisation. The result is a confident, faster path from raw data to meaningful insights, with plenty of “why this works” clarity that demystifies Power Query for readers at all levels.

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