In this session, we will explore real-life examples of dirty data, and the consequences it has on the output, such as decision making, reporting, analytics, AI and machine learning.

The speaker will share with you 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:

The importance of data accuracy
The consequences of dirty data
How to ensure data accuracy
Make sure your data has its COAT on
How to spot check your data

Note: Susan will use excel to show the practical application during the session. However, those techniques can be adapted on any open source software (like R, Python).

The Dangers of Dirty Data and How to Fix It

26th Sep

03:00 PM - 01:15 PM (CUT)

Susan Walsh

About this session

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