Between the Spreadsheets

Classifying and Fixing Dirty Data
2. Auflage 2025
ISBN: 978-1-78330-784-5
Verlag: Taylor & Francis

Buch, Englisch, 222 Seiten, Format (B × H): 156 mm x 234 mm

'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. And with the increasing use of AI and Generative AI, it's only getting worse. 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 best practices on how to fix it.

Fully revised and updated throughout, this new edition of Between the Spreadsheets draws on classification expert Susan Walsh's years of hands-on experience in data 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 framework, 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 and why it is so important to have clean data before using it.

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.

Zielgruppe

Professional Reference

Autoren/Hrsg.

Walsh, Susan

Fachgebiete

• Wirtschaftswissenschaften Betriebswirtschaft Management Wissensmanagement

Inhaltsverzeichnis

Introduction 1. The Dangers of Dirty Data 2. Supplier Normalisation 3. What is a Taxonomy? 4. Spend Data Classification 5. Basic Data Cleansing 6. Before and After: Real-Life Data Cleaning Case Studies 7. The Myth Exposed: Data Cleaning and GenAI 8. Other Methodologies 9. The Dirty Data Maturity Model 10. Data Horror Stories Conclusion

Über Autor(innen)

Susan Walsh is an entrepreneur, female business owner, published author, course creator, award winner and TEDx speaker. And that’s just the beginning. She has a degree in Commerce and spent her early career working for large global corporations. Since 2017, Susan, as The Classification Guru has been cleaning, classifying and fixing dirty data for clients globally, helping them to solve dirty data problems initially in the procurement world, with her reach ultimately growing far beyond into many other industries. As well as an entrepreneur, Susan is an industry thought leader, an influencer and a global speaker. She has been listed in the DataIQ100 for the last two years, as well as winning DataIQ Data Champion 2022 and 2023. She’s also a Key Influencer for the Accounts Payable Association, promoting the benefits of clean data across many industries, and is a finalist for The Great British Businesswoman Awards in the Technology category. She’s the author of Between the Spreadsheets: Classifying and Fixing Dirty Data, which is sold globally, has two online courses based on Fixing and Cleaning Dirty Data for Pluralsight, and O’Reilly. In addition to this, Susan also has a TEDx Talk Say NO to NO about resilience, which has amassed 3k views and counting. She has created the data COAT framework, which has helped companies across the globe save time and money thanks to seeing the value in cleaning their ‘dirty data’, and is about to launch a new supplier normalisation tool “Samification”. She has attended well over a hundred events globally in data, finance and procurement, whether that be as a speaker, an exhibitor, or as an influencer, and is still active in tackling dirty data, helping over 80 clients in the last seven years as The Classification Guru.