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The Data Journey

Roland Brown

The Data Journey: Big Ideas, Small TimeLooking to stay ahead in data architecture, education strategy, and leadership—but short on time?The Data Journey delivers actionable insights in under 10 minutes, weekly. Each episode is designed for busy professionals: quick, practical, and easy to apply. No fluff, no filler—just the strategies and frameworks you need to make smarter decisions, faster.Subscribe to the newsletter at www.thedatajourney.com and transform your coffee break into a mini-masterclass in modern data and leadership.

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98 avsnitt

  1. Episode 98: The Operating Model of an AI-Ready Organisation 8:32
  2. Episode 97: From Use Cases to Value Streams 7:58
  3. Episode 96: Incentives Drive Behaviour (And Kill Data Strategies) 7:38
  4. Episode 95: Organisational Readiness vs Technical Readiness 7:44
  5. Episode 94: Why Most Organisations Can’t Scale AI Beyond Pilots 9:21
  6. Episode 93: The Missing Role: Product Managers for Data & AI 13:30
  7. Episode 92: Funding Models: Why Data & AI Initiatives Stall 9:47
  8. Episode 91: Why Governance Slows Teams Down (And How to Fix It) 16:06
  9. Episode 90: The Role of the Data COE (What It Should Actually Do) 16:17
  10. Episode 89: Data Ownership Is Still Broken (And Why That Matters) 7:58
  11. Episode 88: Centralised vs Federated: What Actually Works in Practice 20:26
  12. Episode 87: Architecture Is Not an Operating Model 14:13
  13. Episode 86: Why Data & AI Strategies Fail in Execution 7:33
  14. Episode 85: From Experimentation to Production AI 11:16
  15. Episode 84: AI Value vs AI Theatre 10:28
  16. Episode 83: When Not to Use AI 10:07
  17. Episode 82: Explainable AI Starts With Architecture 10:23
  18. Episode 81: Governing AI Like a Product 6:27
  19. Episode 80: Human-in-the-loop Design 9:48
  20. Episode 79: Observability for AI Systems 10:51
  21. Episode 78: Data Quality for Machine Learning (Different Rules) 7:25
  22. Episode 77: Metadata and Lineage for AI Explainability 7:36
  23. Episode 76: Training Data vs Inference Data 6:57
  24. Episode 75: The Three Layers of AI-Ready Architecture: Trust, Context, Intelligence 8:28
  25. Episode 74: AI doesn’t fail - data does 7:45
  26. Episode 73: Why AI Exposes Weak Data Foundations 9:21
  27. Episode 72: From Project Delivery to Product Thinking 8:56
  28. Episode 71: Customer 360 as a Data Product: An End-to-End Example 7:55
  29. Episode 70: Data Marketplaces and Discovery: Finding what actually matters 9:29
  30. Episode 69: Killing Bad Data Products: Sunsetting Properly 7:01
  31. Episode 68: Why most data products fail 8:05
  32. Episode 67: Measuring Data Product Success: Reuse, Adoption, and Trust 7:59
  33. Episode 66:Data contracts in practice (not theory) 8:04
  34. Episode 65: Ownership Models: Who Is Accountable for Value? 9:21
  35. Episode 64: Designing Data Products for Consumers, Not Producers 8:56
  36. Episode 63: Data Products vs Reports vs Datasets 8:35
  37. Episode 62: The Anatomy of a Good Data Product 10:32
  38. Episode 61: What a Data Product Really Is (and What It Isn’t) 7:14
  39. Episode 60: Why Pipelines Don’t Deliver Value on Their Own 7:41
  40. Episode 59: Data Culture — Turning Curiosity into Capability 10:46
  41. Episode 58: Data is the Product: Building AI-Ready Data Pipelines 13:19
  42. Episode 57: Observability & SLAs — SLOs, Metrics and Reliability Engineering for Data 8:37
  43. Episode 56: DataOps & Automation — Continuous Data Delivery 6:21
  44. Episode 55: Data Contracts & Semantic Layers — From Agreement to Accountability 7:35
  45. Episode 54: Data Modelling 2.0 — From Entities to Ontologies 8:04
  46. Episode 53: Data Catalogues & Knowledge Graphs — Discovery for Reuse at Scale 7:27
  47. Episode 52: End-to-End Lineage — The X-Ray of Data 8:32
  48. Episode 51: The Metadata Mindset — From Documentation to Automation 7:55
  49. Episode 50: Data Architecture Patterns — The Hidden Frameworks 7:34
  50. Episode 49: Open Data — Sharing to Strengthen Insight 7:54