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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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Toc

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

High cost of poor data quality

There have been many surveys and reports that try to quantify the cost of poor data quality to an organization. Quintly estimates poor data costs an average loss of $15 million per year, while IBM estimated it cost US businesses $3.1 trillion in 2016 alone.6 Meanwhile, in a recent survey commissioned by Monte Carlo, more than half of the respondents reported that poor data quality is impacting 25% or more of their revenue, while the average from all respondents was 31%.7

$15 million Average losses incurred due to poor data quality

25% Or more revenue impacted by poor data quality

These findings outline both the direct and indirect ramifications of poor data quality. Direct costs are those that have an impact in the short term and include the breakdown of an operational process, the downtime of a data-driven product, and the loss of productivity for employees. Indirect costs are those that have an impact over the long term, impacting decision...

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