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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

Bibliography

  1. Informatica, January 31, 2024. “New Research from Informatica Reveals More Data Leaders Plan to Capitalize on Generative AI, but Data Quality Remains the Key Obstacle to Adoption.” https://www.informatica.com/about-us/news/news-releases/2024/01/20240131-new-research-from-informatica-reveals-more-data-leaders-plan-to-capitalize-on-generative-ai-but-data-quality-remains-the-key-obstacle-to-adoption.html
  2. Datiku 2023. “AI, Today: Insights From 400 Senior AI Professionals on Generative AI, ROI, Tech Stack, & More.” https://content.dataiku.com/dataiku-databricks-survey
  3. Twilio Segment, 2023. “The State of Personalization 2023.” https://segment.com/pdfs/State-of-Personalization-Report-Twilio-Segment-2023.pdf
  4. Anaconda, 2022. “2022 State of Data Science.” https://www.anaconda.com/resources/whitepapers/state-of-data-science-report-2022
  5. Jamie Galvin, June 21, 2022. “Unity Software: It’s Not...
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