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Full Description
Struggling to convert your data, analytics and AI strategy into business value?
Data and Analytics Strategy for Business by Simon Asplen-Taylor is an essential guide for CDOs, CAIOs, CIOs and CTOs seeking to deliver measurable results from data investments. Focused on aligning data, analytics and AI with strategic goals, this book helps leaders move from initial implementation to transformation.
Fully updated with the latest AI developments, it provides practical tools and real-world insights to accelerate implementation, drive adoption and optimize performance across the organization.
You'll learn how to:
- Align data, analytics and AI to strategic business outcomes
- Build trust through data quality, governance and transparency
- Integrate AI and ML Secure executive and organizational buy-in for long-term success
- Learn from real-world examples including Tesco and Facebook
With guidance grounded in real results, Data and Analytics Strategy for Business helps senior leaders lead smarter, execute faster and unlock enterprise-wide impact.
Themes include: data strategy, AI adoption, analytics leadership, digital transformation, data governance, performance optimization
Contents
Section - ONE: How data, analytics and AI can help you grow your business;
Chapter - 01: How can this book help you?;
Chapter - 02: The business case for data;
Chapter - 03: Your data and analytics strategy;
Chapter - 04: AI strategy;
Chapter - 05: A team game;
Section - TWO: Wave 1 - aspire;
Chapter - 06: A quick win;
Chapter - 07: Repeat and learn;
Section - THREE: Wave 2 - mature;
Chapter - 08: Data governance;
Chapter - 09: Data quality;
Chapter - 10: Single customer view;
Chapter - 11: Generating insights;
Chapter - 12: Data risk management and ethics;
Section - FOUR: Wave 3 - industrialize;
Chapter - 13: Automation, automation, automation;
Chapter - 14: Scaling up and scaling out;
Chapter - 15: Data and AI culture;
Section - FIVE: Wave 4 - realize;
Chapter - 16: The voice of the customer;
Chapter - 17: Maximizing data science and AI;
Chapter - 18: Sharing data with suppliers and customers;
Section - Six: Wave 5 - differentiate;
Chapter - 19: Data products;
Chapter - 20: Right leadership, right time;
Chapter - 21: Epilogue - data and AI success;
Chapter - 22: Glossary;
