Data Storage

In recent years, the spotlight has been firmly on new data architectures, advanced analytics, and AI-led transformation. These are exciting developments – full of promise and potential. But amid the enthusiasm, it’s easy to overlook the less glamorous, yet absolutely critical, foundation that underpins all of it: data storage.

We often hear about organisations wanting to become data-driven, to deliver insights at scale, or to roll out self-service analytics across the enterprise. But none of this happens without data being reliably stored, discoverable, and accessible when it’s needed. That’s not just a technical detail – it’s the groundwork for any data strategy worth its salt.

In practice, we’re seeing a shift away from traditional approaches to storage. It’s no longer enough to have a centralised warehouse that hoovers up data in the hope that someone might use it. Instead, modern data storage needs to support distributed access, cloud-native scalability, and fast, flexible ingestion frameworks that empower teams to move quickly.

The best storage strategies today are designed around how data will be used, not just how it will be stored. That means thinking about domain-level ownership, interoperability between systems, and governance by design. The right approach gives you a clear view of where your data is, who owns it, and how it can be activated to deliver value. It removes friction between data producers and consumers. It makes data trustworthy by default.

More importantly, effective storage strategy plays a pivotal role in enabling more advanced architectures like Data Mesh. If you’re serious about decentralising data ownership and giving business domains autonomy over their data products, then your storage model needs to support that shift. Otherwise, you end up with bottlenecks, confusion, and a growing gap between ambition and reality.

Of course, it’s not just about infrastructure – it’s also about mindset. If your teams don’t know what data exists, or can’t get to it easily, they’ll resort to building their own copies or working in silos. That’s how duplication, inefficiency, and mistrust creep in. clear documentation, data cataloguing, and robust governance process are just as important as any piece of tech in your stack.

Ultimately, data storage might not be the flashiest part of your data architecture, but it’s arguably the most important. Without the right foundations in place, even the most sophisticated initiatives struggle to deliver consistent business value. On the other hand, getting it right unlocks agility, scalability, and real data-driven culture.

Look out for our Global Head of Data, Borja Ochoa’s deep dive next week, where he explores what it really takes to implement a successful Data Mesh – and why, despite the hype, it’s not a one-size-fits-all approach.