Cleaning and Standardizing Data: Data Quality with Power Query (Analytics at Work)

The pipeline reruns. The cleaning log explains itself.

Dirty data is not a one-off chore — it arrives again next month. This book builds a repeatable cleaning pipeline in Power Query, and in SQL and Python when the volume outgrows it, then proves the cleaning actually worked.

Every defect it treats is measured first on a raw edition of the Cedar Ridge systems, so you clean what is there rather than what you assume is there.

What you will be able to do

• Profile first: a defect inventory measured, not guessed
• Types, missing values, duplicates, outliers and implausible values
• Record matching, entity resolution, names, addresses, currency and units
• Validation rules and a cleaning log somebody else can audit
• When not to clean — and how to say so out loud

Who it is for

Anyone who receives data from somebody else and is held responsible for what comes out of it.

The labs

Every chapter ends with a practice lab. Each one can be worked in the tools you already have, or in a free browser version that checks your answer as you go — no account, no install. The address is printed inside the book.

About the series

Analytics at Work is an eight-book series for business professionals. All eight run on the same thirty-six months of enterprise data from Cedar Ridge Brands, a fictional American consumer-goods maker. This is Book 3 of 8.