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The Great Data Observability Debate: Revolutionary Framework or Expensive Fiction?

  • Writer: Daniel Rolles
    Daniel Rolles
  • Oct 4
  • 3 min read

The Trigger: Last week, following the release of Claude Sonnet 4.5 and the continued conversations at major industry events (see our posts on Big Data London), I found myself asking a critical question: *Are we selling genuine innovation, or just repackaging old ideas with new terminology?*


The stakes are too high to rely on untested assumptions. So I decided to subject our Data & Information Observability framework to the harshest possible scrutiny—not from a friendly colleague or a supportive client, but from one of the world's most advanced AI systems programmed to tear my arguments apart.


I turned to Claude Sonnet 4.5 and gave it a simple instruction: play the ultimate sceptic and destroy my definition of D/I Observability. No holds barred. Find every weakness, every contradiction, every hint of consulting jargon masquerading as substance.


What followed was one of the most intellectually challenging conversations I've had about our framework. Below is the complete, unedited exchange—a raw look at how our ideas hold up under relentless questioning.



The Framework Under Fire


Our Definition of Data & Information Observability:

"The capabilities to observe and steward Data and Information assets across their entire lifecycle, enabling organisations to understand health, performance, and impact whilst maintaining strategic alignment with business objectives."

The Debate Exchange



Reflections: What This Debate Revealed


This exchange, even with an AI, was profoundly clarifying. The critic's skepticism wasn't just obstruction—it was a necessary crucible that forced Data & Information Observability to evolve from abstract concept to defensible position.


The most critical insight: The future isn't about choosing between governance and observability. They are not in opposition.


It's Governance + Observability.


Governance provides the framework, the policies, the "what we need to do." Observability provides the instrumentation, the real-time feedback, the "proof that we are doing it." One without the other is incomplete.


Governance without observability is blind.

Observability without governance is chaos.


The path forward is clear: weave observability into the fabric of governance frameworks, making them executable, measurable, and ultimately, successful.



Your Perspective Matters


I'm sharing this debate with a select group of data leaders before wider publication.


I'd genuinely value your input on:


  • Did the debate format clarify or confuse the D/I Observability concept?

  • Which arguments resonated most strongly with you?

  • What objections would *your* organization raise?

  • Would you share this with colleagues? Why or why not?

  • Does this position BearingNode as a thought leader or as too theoretical?


Honest feedback is most valuable. This is meant to provoke thought and refine our messaging before broader publication.



About the Author

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Daniel Rolles is the CEO and Founder of BearingNode, where he leads the firm's mission to help organisations unlock the commercial value of their data whilst enhancing their risk management capabilities.


As CEO, Daniel drives BearingNode's strategic vision and thought leadership in data transformation, analytics strategy, and the evolving regulatory landscape. He regularly shares insights through industry publications and speaking engagements, focusing on practical approaches to data governance, AI implementation, and performance transformation in regulated environments. He is one of the key authors of BearingNode's Data and Information Observability Framework.


With over 30 years of experience in Data, Analytics and AI, Daniel has successfully built and led D&A teams across multiple industries including Financial Services (investment, commercial and retail banking, investment management and insurance), Healthcare, and Real Estate. His expertise spans consulting, commercial leadership, and delivery management, with a particular focus on data governance and regulatory compliance.


Daniel holds a Bachelor of Economics (University of Sydney), Masters of Science (Birkbeck College, University of London), and Executive MBA (London Business School).


Based in London, Daniel is passionate about financial inclusion and social impact. He serves as a Trustee for Crosslight Advice, a debt advisory and financial literacy charity based in West London that provides vital support to individuals facing financial vulnerability.


Connect with Daniel on LinkedIn or learn more about BearingNode's approach to data and analytics transformation at BearingNode.



Note: Claude Sonnet 4.5 is an AI assistant developed by Anthropic. Claude is a trademark of Anthropic PBC.



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