Data Quality in the Age of AI: Building a foundation for AI strategy and data culture

As organizations worldwide seek to revamp their data strategies to leverage AI advancements and benefit from newfound capabilities, data quality emerges as the cornerstone for success. Without high-quality data, even the most advanced AI models falter. Enter Data Quality in the Age of AI, a detailed report that illuminates the crucial role of data quality in shaping effective data strategies.
Packed with actionable insights, this report highlights the critical role of data quality in your overall data strategy. It equips teams and organizations with the knowledge and tools to thrive in the evolving AI landscape, serving as a roadmap for harnessing the power of data quality, enabling them to unlock their data's full potential, leading to improved performance, reduced costs, increased revenue, and informed strategic decisions.

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Data Quality in the Age of AI: Building a foundation for AI strategy and data culture

As organizations worldwide seek to revamp their data strategies to leverage AI advancements and benefit from newfound capabilities, data quality emerges as the cornerstone for success. Without high-quality data, even the most advanced AI models falter. Enter Data Quality in the Age of AI, a detailed report that illuminates the crucial role of data quality in shaping effective data strategies.
Packed with actionable insights, this report highlights the critical role of data quality in your overall data strategy. It equips teams and organizations with the knowledge and tools to thrive in the evolving AI landscape, serving as a roadmap for harnessing the power of data quality, enabling them to unlock their data's full potential, leading to improved performance, reduced costs, increased revenue, and informed strategic decisions.

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Data Quality in the Age of AI: Building a foundation for AI strategy and data culture

Data Quality in the Age of AI: Building a foundation for AI strategy and data culture

by Andrew Jones
Data Quality in the Age of AI: Building a foundation for AI strategy and data culture
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Data Quality in the Age of AI: Building a foundation for AI strategy and data culture

Data Quality in the Age of AI: Building a foundation for AI strategy and data culture

by Andrew Jones

Overview

As organizations worldwide seek to revamp their data strategies to leverage AI advancements and benefit from newfound capabilities, data quality emerges as the cornerstone for success. Without high-quality data, even the most advanced AI models falter. Enter Data Quality in the Age of AI, a detailed report that illuminates the crucial role of data quality in shaping effective data strategies.
Packed with actionable insights, this report highlights the critical role of data quality in your overall data strategy. It equips teams and organizations with the knowledge and tools to thrive in the evolving AI landscape, serving as a roadmap for harnessing the power of data quality, enabling them to unlock their data's full potential, leading to improved performance, reduced costs, increased revenue, and informed strategic decisions.

Product Details

ISBN-13: 9781835088562
Publisher: Packt Publishing
Publication date: 08/01/2024
Sold by: Barnes & Noble
Format: eBook
Pages: 50
File size: 1 MB

About the Author

Andrew Jones is a Principal Engineer, author, and a Google Developer Expert. He has over 15 years' experience in the industry, with the first half primarily as a software engineer before moving into the data platform and data engineering space. He thinks a lot about how to build platforms - particularly data platforms - that drive the creation of business value. His work on building performant, efficient, and well governed data platforms that facilitate the production and consumption of quality data led him to coining and defining data contracts, and in 2023 he authored the seminal book on the topic, Driving Data Quality with Data Contracts. Andrew is a regular speaker and writer, and passionate about helping organizations get the most value from data.

Table of Contents

Table of Contents
  1. Executive Summary
  2. Introduction: Understanding data quality
  3. Unlocking AI's potential with Data
  4. Improving data quality at the source
  5. Case studies: Positive impact of data quality
  6. Cultivating a data culture that values quality
  7. Conclusion: Embracing a quality-driven data culture
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