Building a Data Culture: The Usage and Flow Data Culture Model

In today's fast-paced digital landscape, organizations face an ever-increasing volume of data that holds immense potential for driving business success. However, many businesses struggle to harness this potential due to a lack of understanding and effective utilization of data within their culture. This book is a comprehensive guide that unveils the transformative power of data and provides actionable insights to cultivate a data-driven organizational culture.

The book emphasizes data strategy and data governance's pivotal role in cultivating a mature data culture using practical insights, frameworks, and best practices. This approach ensures robust data culture structures that uphold data integrity, accessibility, and accountability. These structures operate on the people, processes, and technology through analytics, literacy, governance, process management, and data inventory management.

The authors introduce the groundbreaking Usage and Flow Data Culture Model, a unique framework that enables organizations to evaluate and reshape their data culture based on distinct cultural types: Preservationist, Protectionist, Traditionalist, and Progressive. Each culture type is carefully dissected, revealing associated challenges and opportunities, uncovering suitable strategies in the process.

Developing a worthy data culture necessitates a shift in mindset and the development of relevant skills across the organization. Building a Data Culture is your roadmap to fostering data literacy, promoting data-driven decision-making, and cultivating a data-driven mindset.

What You'll Learn

• Assess your organization's current data culture
• Identify cultural strengths and weaknesses within your organization
• Develop a data governance program
• Define data policies and standards and establish decision-making processes

Who This Book is For

Professionals and leaders across various industries who are interested in building a data culture within their organizations. The typical reader may have a background in data management, analytics, business intelligence, or technology, but the book is designed to be accessible to a wide range of readers with varying levels of expertise.