Data and Analytics Strategy for Business
eBook - ePub

Data and Analytics Strategy for Business

Leverage Data and AI to Achieve Your Business Goals

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

Data and Analytics Strategy for Business

Leverage Data and AI to Achieve Your Business Goals

About this book

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

Trusted by 375,005 students

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Information

Publisher
Kogan Page
Year
2025
Print ISBN
9781398622012
Edition
2
eBook ISBN
9781398622029

Table of contents

  1. List of figures and tables
  2. About the author
  3. Preface
  4. Acknowledgements
  5. PART ONE How data, analytics and AI can help you grow your business
  6. 01 How can this book help you?
  7. 02 The business case for data
  8. 03 Your data and analytics strategy
  9. 04 AI strategy
  10. 05 A team game
  11. PART TWO Wave 1: Aspire
  12. 06 A quick win
  13. 07 Repeat and learn
  14. PART THREE Wave 2: Mature
  15. 08 Data governance
  16. 09 Data quality
  17. 10 Single customer view
  18. 11 Generating insights
  19. 12 Data risk management and ethics
  20. PART FOUR Wave 3: Industrialize
  21. 13 Automation, automation, automation
  22. 14 Scaling up and scaling out
  23. 15 Data and AI culture
  24. PART FIVE Wave 4: Realize
  25. 16 The voice of the customer
  26. 17 Maximizing data science and AI
  27. 18 Sharing data with suppliers and customers
  28. PART SIX Wave 5: Differentiate
  29. 19 Data products
  30. 20 Right leadership, right time
  31. Epilogue: Data and AI success
  32. Glossary
  33. Index

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