We're sorry. An error has occurred
Please cancel or retry.
Between the Spreadsheets

Some error occured while loading the Quick View. Please close the Quick View and try reloading the page.
- Format:
-
02 October 2025

‘Clear, concise, engaging and entertaining. Highly recommended for anyone involved with data in any capacity.' Information Professional
Dirty data is a problem that costs businesses thousands, if not millions, every year. In organisations large and small across the globe you will hear talk of data quality issues. What you will rarely hear about is the consequences or how to fix it.
Fully revised and updated throughout, this new edition of Between the Spreadsheets draws on classification expert Susan Walsh’s decade of experience in data classification to present a fool-proof method for cleaning and classifying your data. The book covers everything from the very basics of data classification to normalisation and taxonomies, and presents the author’s proven COAT methodology, helping ensure an organisation’s data is Consistent, Organised, Accurate and Trustworthy. A series of data horror stories outlines what can go wrong in managing data, and if it does, how it can be fixed as well as new advice on using GenAI.
After reading this book, regardless of your level of experience, not only will you be able to work with your data more efficiently, but you will also understand the impact the work you do with it has, and how it affects the rest of the organisation. Written in an engaging and highly practical manner, Between the Spreadsheets, 2nd Edition gives readers of all levels a deep understanding of the dangers of dirty data and the confidence and skills to work more efficiently and effectively with it.

BUSINESS & ECONOMICS / Information Management, Business strategy, COMPUTERS / Business & Productivity Software / Spreadsheets, COMPUTERS / Data Science / Data Analytics, Library, archive and information management, Data science and analysis: general, Data warehousing, Data mining, Information retrieval

Introduction
- The Dangers of Dirty Data
- Supplier Normalisation
- What is a Taxonomy?
- Spend Data Classification
- Basic Data Cleansing
- Before and After: Real-Life Data Cleaning Case Studies
- The Myth Exposed: Data Cleaning and GenAI
- Other Methodologies
- The Dirty Data Maturity Model
- Data Horror Stories
Conclusion