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Data Quality in the Age of AI

You're reading from   Data Quality in the Age of AI Building a foundation for AI strategy and data culture

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Product type Paperback
Published in Aug 2024
Publisher Packt
ISBN-13 9781805121435
Length 50 pages
Edition 1st Edition
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Author (1):
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Andrew Jones Andrew Jones
Author Profile Icon Andrew Jones
Andrew Jones
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Table of Contents (13) Chapters Close

1. Data Quality in the Age of AI
2. Executive summary FREE CHAPTER 3. Understanding data quality 4. Unlocking AI’s potential with data 5. Improving data quality at the source 6. Case studies: Positive impact of data quality 7. Cultivating a data culture that values quality 8. Conclusion: Embracing a quality-driven data culture
9. About the author
10. About the technical reviewers
11. Additional reading 12. Other Books You May Enjoy 13. Bibliography

Understanding data quality

Organizations everywhere are looking to refresh their data strategies to take advantage of the recent advances in AI and position themselves to capitalize on the newly available capabilities. However, no matter how advanced AI models get, they’ll rely on quality data to be effective. New research from Informatica concluded that 42% of data leaders cite data quality as their top obstacle, while 40% highlight data privacy and governance, and 38% point to AI ethics as significant challenges.1

The quality of your data is not going to improve without a strategy that clearly articulates why doing so is critical for your organization to achieve its AI goals. This report gives you everything you need to clearly articulate why you need to focus on the quality of your data as a key part of your overall data strategy. You will also discover some direct and applicable actions you can take to make data quality the foundation of your data culture.

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You have been reading a chapter from
Data Quality in the Age of AI
Published in: Aug 2024
Publisher: Packt
ISBN-13: 9781805121435
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