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Neil Strange

CEO of Business Thinking and Chair of the Data Community







Bio

Neil Strange is the Chairman of the Data Vault User Group and a seasoned data modelling expert. With decades of experience and training under industry pioneers, Neil has a deep understanding of the intricacies of data modelling. He is passionate about helping organizations improve their data practices and adapt to agile methodologies.

Previous Community Presentations

When Business Transformation Outruns the Data

When Business Transformation Outruns the Data

When business moves faster than BI, trusted data and timely insights become critical. Discover how organisations can modernise their BI capabilities to support rapid decision-making, leadership change, and business transformation.
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From Data Foundations to AI Impact: Building Trust, Scale & Value

From Data Foundations to AI Impact: Building Trust, Scale & Value

Many companies struggle with AI because their data foundations aren’t ready. This talk highlights why clarity, governance and good data management matter more than any single tool.
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Data Mesh and Data Vault – Never the Twain shall meet?

Data Mesh and Data Vault – Never the Twain shall meet?

Contrasting Data Mesh with Data Vault highlights tensions between decentralised ownership and structured enterprise modelling in modern data architectures.
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The things I wish I knew before I started my first Data Vault Project!

The things I wish I knew before I started my first Data Vault Project!

Early Data Vault implementations frequently expose avoidable design and delivery challenges that later inform more robust modelling and architectural decisions.
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Data Vault Modelling

Data Vault Modelling

Structured Data Vault modelling provides a consistent framework for integrating complex enterprise data while maintaining scalability and traceability across systems.
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Introduction to Data Vault 2.0

Introduction to Data Vault 2.0

Data Vault 2.0 extends core modelling principles with stronger automation, agility and governance to support modern enterprise data ecosystems at scale.
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From Semantic Foundation to Trusted AI: What Data Vault Practitioners Need to Know About Building AI That Actually Works

From Semantic Foundation to Trusted AI: What Data Vault Practitioners Need to Know About Building AI That Actually Works

Using real-world AI and analytics scenarios, Julien, Alex and Neil demonstrate how Data Vault provides the governance, semantics and traceability required to support trustworthy AI initiatives.
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Common Challenges with Data Vault Modelling REVISITED

Common Challenges with Data Vault Modelling REVISITED

Neil Strange explores the real‑world obstacles that complicate Data Vault modelling and provides actionable insights to help teams balance abstraction, design effective hubs and links, and build more reliable data platforms.
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5 most common challenges with Data Vault modelling

5 most common challenges with Data Vault modelling

From modelling complexity to integration overhead, recurring Data Vault challenges reveal where architecture decisions most affect long-term maintainability.
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Data Vault: What's it all about

Data Vault: What's it all about

At its core, Data Vault is a modelling methodology designed to structure enterprise data for scalability, traceability and adaptable integration across systems.
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Building the Business Case

Building the Business Case

A well-structured business case connects data initiatives to measurable value, helping organisations justify investment and align stakeholders on delivery outcomes.
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Welcome to the Data Community

Welcome to the Data Community

From punch cards to AI‑assisted platforms, Neil Strange explains why today’s data teams must shift from hand‑coding to orchestration and apply stronger governance and critical judgment.
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The future of Business Intelligence

The future of Business Intelligence

Evolving BI systems are moving toward more automated, real-time and integrated architectures that enhance decision-making and reduce analytical latency across organisations.
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Reference Architecture for Data Vault on Snowflake with Azure

Reference Architecture for Data Vault on Snowflake with Azure

Combining Snowflake with Azure services creates a cloud-native foundation for Data Vault architectures built around scalability, orchestration and platform interoperability.
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Data Vault: Business Rule Secrets

Data Vault: Business Rule Secrets

Embedding business rules within Data Vault structures clarifies how enterprise logic is applied, supporting consistent interpretation and scalable data processing.
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Unlocking Data Vault

Unlocking Data Vault

Overcoming common adoption challenges enables organisations to better realise the benefits of Data Vault through clearer design practices and improved delivery alignment.
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