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The Dangers of Dirty Data and How to Fix It

In this session, Susan Walsh will share how to make quick, accurate checks and changes to your own data in Excel, regardless of your level of experience and implement best practices.
Course info
Level
Intermediate
Updated
Oct 27, 2020
Duration
36m
Table of contents
The Dangers of Dirty Data and How to Fix It
Description
Course info
Level
Intermediate
Updated
Oct 27, 2020
Duration
36m
Description

We all think we know what bad data looks like, but what is it and what are the consequences? Susan Walsh, The Classification Guru, has spent nearly a decade classifying, normalising and cleansing spend data and will share real-life examples of dirty data, and the consequences it has on the output, such as decision making, reporting, analytics, AI and machine learning. She will share how to make quick, accurate checks and changes to your own data in Excel, regardless of your level of experience, explain why data accuracy and maintenance is so important, and implement best practices for this. Takeaways include: The importance of data accuracy, the consequences of dirty data, how to ensure data accuracy, knowing how to make sure your data has its COAT on, and how to spot check your data.

About the author
About the author

Big Data LDN is the UK’s largest data and analytics conference and exhibition.

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