Building a Data Culture
Description
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, Traditional, 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.
Reviews / Votes
"Building a data culture provides an introduction to the concepts of organizational culture and data culture. ... this book introduces the foundational concepts of organizational and data culture. It stresses the need to shape a data culture that complements the existing organizational culture and strategy. The rest of the book provides practical frameworks, strategies, and real-world examples for building a thriving data culture." (R. S. Chang, Computing Reviews, April 5, 2024)
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Persons
Gary W. Griffin is a noted author, speaker, innovator and consultant who has spent over 30 years in the public and private sectors delivering enterprise solutions that focus on data, analytics, and strategy. He is the inventor of Datalink 1000, a Master Data Management and Data Quality tool. He also developed the data strategy for one of the first web-based assessment systems for K-12 education. Dr. Griffin has a Master of Science and a Doctor of Philosophy in Sociology.
David Holcomb is a speaker, writer, practitioner, and theorist in data warehousing, business intelligence, organizational behavior and culture, and cyber security. His career includes leadership roles in business operations, marketing, sales, product development, and information technology at leading brands, including Verizon, Western Union, and University of Chicago Medicine. Dr. Holcomb holds a Master of Science in Management Information Systems, a Doctor of Philosophy inBusiness Administration, and a Doctor of Philosophy in Information Technology.
Content
1. Data Culture.- 2. The Current State.- 3. Organizational Vision and Data Strategy.- 4. Leadership and Change Management.- 5. Data Governance and Infrastructure.- 6. Data Literacy and Skills Development.- 7. Embedding Data into Decision Making.- 8. Nurturing Collaboration and Communication.- 9. Measuring Success and Sustaining the Data Culture.- 10. Case Studies and Lessons Learned.