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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

DoorDash

Today, DoorDash is the largest food delivery platform in the US, but that hasn’t always been the case. In January 2018, DoorDash had just 17% share of a super-competitive market, competing against many well-funded competitors.

Food delivery is a low-margin business, so not only did they need to increase market share, but they also needed to increase profitability on every order.

By October 2020, DoorDash had achieved 50% market share, and much of their success has been attributed to their investment in data quality, data platforms, and AI.

DoorDash has invested heavily in a data platform11 with a focus on:

  • Reliability, quality, and SLAs: DoorDash has recognized the importance of detecting and monitoring the quality of their data and catching any problems as early as possible. This reduces the time to recovery and the associated costs—particularly when dealing with data at scale.
  • Prioritizing trust in data: DoorDash sees...
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