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

Unlock the power of data with expert insights to enhance data quality, maximizing the potential of AI, and establishing a data-centric culture
Key Features

• Gain a profound understanding of the interplay between data quality and AI
• Explore strategies to improve data quality with practical implementation and real-world results
• Acquire the skills to measure and evaluate data quality, empowering data-driven decisions

Book Description
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.
What you will learn

• Discover actionable steps to establish data quality as the foundation of your data culture
• Enhance data quality directly at its source with effective strategies and best practices
• Elevate data quality standards and enhance data literacy within your organization
• Identify and measure data quality within the dataset
• Adopt a product mindset to address data quality challenges
• Explore emerging architectural patterns like data mesh and data contracts
• Assign roles, responsibilities, and incentives for data generators
• Gain insights from real-world case studies

Who this book is for
This report is for data leaders and decision-makers, including CTOs, CIOs, CISOs, CPOs, and CEOs responsible for shaping their organization's data strategy to maximize data value, especially those interested in harnessing recent AI advancements.
Table of Contents

• Executive Summary
• Introduction: Understanding data quality
• Unlocking AI's potential with Data
• Improving data quality at the source
• Case studies: Positive impact of data quality
• Cultivating a data culture that values quality
• Conclusion: Embracing a quality-driven data culture