In this episode, Neil Strange and Alex Higgs dive into the real-world pain of working with XML. From legacy systems and unreadable schemas to bloated file sizes and broken audit trails, Alex shares the kind of problems that don’t show up in the docs—but definitely show up in your project timelines.

✅ What you'll learn:
Why XML still shows up in modern data pipelines
The key differences between XML and JSON
How XSD helps (and hurts) when validating XML
Common XML mistakes that break audits and slow down delivery
When to fight for JSON instead

⏱️ Chapters
00:00 – Intro
00:14 – Why XML is a “necessary evil”
01:00 – XML vs JSON: key differences
01:18 – When you're forced to use XML
02:08 – Why JSON is usually easier to work with
02:22 – What is XSD and why does it matter?
03:10 – Hidden pitfalls: empty tags and missing elements
04:05 – Why XML breaks in production
05:00 – Real-world XML horror stories
06:01 – Data quality and governance issues
06:44 – Missing keys and broken audit trails
07:12 – Should you always choose JSON?
07:30 – Final thoughts + join the debate

📢 Got strong feelings about XML or JSON? Let us know in the comments.
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In this episode, Neil Strange and Alex Higgs tackle one of the most misunderstood steps in building a data warehouse: landing the data.

From internal systems to APIs and SaaS tools, this isn’t just a technical job—there’s politics, governance, and reliability to think about.

They cover:
 🔁 Push vs Pull
 🔒 Access challenges
 🧰 Tools (Fivetran, Airbyte, etc.)
 🧪 When to build vs buy
 🧾 CDC and data quality risks
 🗂 PSAs and staging areas

Whether you're starting fresh or scaling pipelines, this will save you headaches.

👇 Chapters:
00:00 - Intro
00:40 - What does “landing data” mean?
02:10 - Push vs Pull: Definitions and differences
05:15 - Which is more reliable in practice?
08:30 - Political barriers to pulling data
10:45 - Why access isn’t just a technical issue
13:00 - Common tools: Fivetran, Airbyte, Matillion
15:20 - When those tools fall short
17:00 - Should you build your own pipelines?
19:10 - Change Data Capture (CDC) explained
21:30 - Handling deletes, updates, and historical tracking
24:05 - Persistent Staging Areas: Why they matter
26:50 - Final thoughts and key takeaways

👉 Subscribe for more on data architecture, ETL, and real-world data warehousing.

For more expert insights, check out our services designed to help organizations like yours unlock the full potential of Data Vault.
👉 Explore our training courses to level up your data management skills: https://bit.ly/4eNkczq
👉 Download our free Data Vault resources: https://bit.ly/4f9AYs9
👉 Book a free consultation with our team: https://bit.ly/3BT6VXC

In this episode, we tackle a common challenge for modern data teams: What should you do with all that JSON and other semi-structured data flooding in from APIs, events, and third-party sources?

We break down when to store, when to split, and how to stay sane in a world of endlessly nested payloads.

📌 Chapters:

00:00 – Introduction

00:10 – Why semi-structured data is everywhere

01:02 – Store vs. split: making the right call

03:15 – Handling schema drift and variants

05:24 – Data contracts and API payload challenges

07:41 – Tips for integrating JSON in your warehouse

09:06 – Common mistakes to avoid

10:00 – Key takeaways & next steps

For more expert insights, check out our services designed to help organizations like yours unlock the full potential of Data Vault.
👉 Explore our training courses to level up your data management skills: https://bit.ly/4eNkczq
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 In this episode of the Business Thinking Podcast, we sit down with Joe Barter, one of our in-house analysts and data modelling experts, to tackle a hands-on question: “How do I actually start a data model?” Whether you're staring at a blank whiteboard or trying to wrangle ideas into a structure, we break down how to move from chaos to concepts — with practical tips, process thinking, and a little help from GenAI. 

For more expert insights, check out our services designed to help organizations like yours unlock the full potential of Data Vault.
👉 Explore our training courses to level up your data management skills: https://bit.ly/4eNkczq
👉 Download our free Data Vault resources: https://bit.ly/4f9AYs9
👉 Book a free consultation with our team: https://bit.ly/3BT6VXC

In this episode of the Business Thinking Podcast, we sit down with Joe, our in-house data modelling expert, to unpack a common but crucial question: "When is the right time to use Data Vault?" From business readiness to migrations and AI integrations, we explore the key indicators that tell you when your organisation is ready to get value from Data Vault — and when it might not be the right fit just yet. 

For more expert insights, check out our services designed to help organizations like yours unlock the full potential of Data Vault.
👉 Explore our training courses to level up your data management skills: https://bit.ly/4eNkczq
👉 Download our free Data Vault resources: https://bit.ly/4f9AYs9
👉 Book a free consultation with our team: https://bit.ly/3BT6VXC

In this episode, we tackle a critical question for data professionals: When is Data Vault not the best choice for building a data warehouse?

For more expert insights, check out our services designed to help organizations like yours unlock the full potential of Data Vault.
👉 Explore our training courses to level up your data management skills: https://bit.ly/4eNkczq
👉 Download our free Data Vault resources: https://bit.ly/4f9AYs9
👉 Book a free consultation with our team: https://bit.ly/3BT6VXC

In this episode, our CEO, Neil Strange, sits down with Joe Barter, our specialist in data modelling and analysis, to unpack the role of data modelling in modern organizations. We explore whether it's still a critical skill, and why it might be more relevant than ever.

For more expert insights, check out our services designed to help organizations like yours unlock the full potential of Data Vault.
👉 Explore our training courses to level up your data management skills: https://bit.ly/4eNkczq
👉 Download our free Data Vault resources: https://bit.ly/4f9AYs9
👉 Book a free consultation with our team: https://bit.ly/3BT6VXC

In this episode, Neil Strange and Alex discuss the importance of data literacy and what it takes to build a truly data-driven organisation. They cover everything from understanding basic data concepts to using the right tools and applying critical thinking when analysing data.

🔔 Subscribe for more insights on data engineering and data warehousing!

For more expert insights, check out our services designed to help organizations like yours unlock the full potential of Data Vault.
👉 Explore our training courses to level up your data management skills: https://bit.ly/4eNkczq
👉 Download our free Data Vault resources: https://bit.ly/4f9AYs9
👉 Book a free consultation with our team: https://bit.ly/3BT6VXC