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The Only Constant

Episode #24 | Susan Walsh | Data quality and its critical role in the success of AI

Jun 20, 2024
48:22
In this episode of The Only Constant, Lasse Rindom speaks with Susan Walsh about the pervasive issue of data quality and the critical role it plays in the success of AI and organizational efficiency. Susan, an expert in data classification and cleaning, shares her insights on the necessity of prioritizing clean data and the complexities of managing master data across different departments.

In this conversation, you will gain insights into:
  • How data issues are a universal problem in organizations and the importance of making data cleanliness a priority.
  • The critical link between AI effectiveness and data quality, highlighting why clean data is the cornerstone of reliable AI outputs.
  • The complexities of master data management, particularly in procurement versus finance, and the need for tailored data strategies within various business functions.  

Do you want to learn more about Susan Walsh?
Susan Walsh is The Classification Guru. She has been cleaning, classifying and fixing dirty data for over a decade and set up The Classification Guru Ltd 2017 to solve dirty data problems in the procurement world.

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.

She’s a published author of Between the Spreadsheets: Classifying and Fixing Dirty Data and has her own online course: Fixing Dirty Data – The Basics of Data Cleaning. In addition to this, Susan also has a TEDx Talk Say NO to NO about resilience, which has amassed 3k views and counting.

Susan 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’.

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