Building a joined-up view of your organisation using Data Vault

Rhys Hanscombe
Sep 5, 2023
2 min read

At the 2023 Data Vault Conference, Neil Sparrow shared Adaptavist’s real-world journey of adopting Data Vault to create a unified, scalable, and business-friendly data platform. If you missed it, here’s your friendly recap—and a reminder to join our forum to keep the conversation going!

Why Data Vault? Breaking Down Silos, Building for Scale

Adaptavist faced the classic challenges: a backlog of data/reporting requests, slow turnaround times, and scalability issues across people, process, and technology. The team realized that to answer the “big questions” and avoid data silos, they needed to model the organization as a whole, not just at the department level. Data Vault offered a standardized, scalable methodology and a way to evolve their architecture for the future.

People, Process, and Technology: The Hub & Spoke Model

From Centralized to Embedded: Moving from a central data team to embedded analysts in each business unit, leveraging domain knowledge and SQL/data skills.
Data as a Product: Treating internal customers like external ones, offering “data as a product” and “modelling as a product” alongside traditional reporting.
Hub & Spoke: Exporting capability and knowledge, not just importing domain expertise.

Kimball vs. Data Vault: Why Not Both?

Data Vault: Focuses on integration and loading, providing a robust foundation for a single source of truth.
Kimball/Star Schema: Optimized for querying and reporting.
Best of Both: Adaptavist uses Data Vault for integration and Kimball for the presentation layer, combining strengths for a flexible, future-proof architecture.

Lessons from Implementation: Start Small, Learn Fast

First Delivery: Released a new data product and made stakeholders happy, but learned that modeling is 95% of the work—coding is (relatively) simple.
Key Takeaways: Decouple learning Data Vault from project deadlines, lean on experts, and focus on modeling. Grow skills in the background and bring modeling in at the right stage of your data stack’s evolution.
Be Kind: Everyone gets it wrong sometimes—be nice and support each other

The Future: Data Vault as a Centralized Data Hub

Not just for reporting: Data Vault becomes the backbone for a centralized data hub, supporting deduplication, “right to forget,” and a single source of truth.
Data Mesh Ready: Adaptavist is looking ahead to data mesh architectures, with Data Vault as the foundation for a joined-up, organization-wide view.

Key Messages for Data Vault Customers

Start small and show success: Build confidence in your delivery teams.
Lean on experts and manage risk: Decouple learning from project pressure when possible.
Focus on modeling: It’s the heart of Data Vault success.
People, process, technology: Bring all three together for the best results.
Be supportive: Mistakes happen—help each other learn and grow.

Join the Data Community!

Sign up to our forum: Share your experiences, ask questions, and connect with fellow data enthusiasts.
Stay up to date: We host regular webinars, workshops, and meetups—don’t miss out!
Shape the future: Your feedback and participation help us build better tools and resources for everyone.

Final Thoughts

Building a joined-up view of your organization is a journey—one that’s easier (and more fun!) with the right methodology, tools, and community support. Ready to get started? Join the conversation, sign up for our next webinar, and let’s build the future of data together!