The modern data stack is essentially a cloud-based way of handling your organisation’s data – from how it’s collected, to how it’s stored, transformed and used to drive business decisions. Compared to older, on-premise setups that are often rigid and fragmented, the modern data stack is flexible, scalable and built to serve the entire organisation.
Often, businesses begin their data journey with a few standalone use cases. Maybe marketing builds their own dashboards, or finance runs ad hoc reports. That’s fine to start with, but without a shared foundation, things can quickly get messy. You end up with disconnected systems, duplicated logic, and different answers to the same question. And that’s where trust in data breaks down.
A well-architected modern data stack brings everything together into a single, unified approach – designed not just for today’s use case, but for whatever comes next.
Why the modern data stack matters
Data on its own doesn’t change anything. The value lies in how it’s used. If you’re a business leader asking, “How many units did we sell last month?” you need an answer that’s not just quick, but reliable.
That question often crosses multiple teams. If each team is running their own tools and reports, the numbers won’t match. One dashboard might say 7,000, another says 7,500, and now no one trusts either.
That’s the cost of not having a well-structured data foundation. The modern data stack solves this by centralising data, standardising how it’s transformed and making it accessible to the right people at the right time. When it’s working properly, it moves your organisation from gut feel to genuine insight.
Modern data stack architecture, roles and tools: how it all fits together
The modern data stack is built in layers - and each layer has its own purpose, tools and people.
It starts with data engineering. This is getting data into your system. Data engineers extract information from source systems like your CRM, finance platform or marketing tools, and move it into a centralised data warehouse. At Cobry, we work primarily with Google BigQuery, a secure, scalable and cloud-native warehouse that forms the core of most modern stacks.
Then comes analytics engineering – the layer between raw data and insights. The goal here is to shape and transform data into something useful. Analytics engineers write the logic, clean up inconsistencies, and build business-friendly models. This is also where data modelling happens: structuring datasets to reflect how the business works and making them easier to analyse.
Finally, you have data analytics - the part most people see. This is where dashboards, reports and KPIs live. It’s also where business users go to explore and understand the data. In the Google Cloud camp, we use Looker to bring this layer to life, enabling teams to ask and answer their own questions using governed, trusted data.
These three layers align with the core roles found in most data teams:
Data engineers keep things flowing
Analytics engineers make the data usable
Data analysts focus on insight and impact
Each layer builds on the one before. If the early foundations aren’t solid, everything further up the stack becomes harder to maintain and scale.
The tools in your stack don’t have to be identical to everyone else’s - but they do need to work together. At Cobry, we recommend Google Cloud-native tooling because it’s simple to manage, scalable from day one, and doesn’t require endless integrations or workarounds. Each tool does its job well, but it’s how they work together that creates long-term value.
Modern data analytics is more than just tools
We often say that data maturity is more about people than platforms. You can have all the best tools in the world, but if no one is using them, or if only a small group understands how the data flows, you’re not getting the value you should.
One of the key signs of a mature data organisation is how many people are actively using data – not just your analysts, but your sales teams, operations, finance, even customer support. Can they access the data they need? Can they trust it? Are they empowered to explore it themselves, or waiting on someone to build a report for them?
Modern data analytics is about creating a culture where data is accessible, trusted and actively used to make decisions. Not hoarded or hidden behind ticket queues.
Build for now… Plan for scale
At Cobry, we care about more than just setting up systems. We care about removing the friction between people and data.
Yes, it’s important to get quick wins. But how you build that first dashboard or solve that first problem matters. Done right, it becomes the foundation your whole team can build on.
We want organisations where data drives decisions at every level. Where your CEO can forecast confidently, your sales team can track targets without waiting, and your finance team isn’t chasing last month’s numbers.
We always start with a free Data Maturity Workshop. This allows us to get a clear picture of where you are, what’s working, and where the gaps are. From there, we build a data stack that delivers today and can grow with your ambitions.
If your current setup is holding you back, learn more about how we can make data work better for your team.
