If you are designing data systems and they are going to hold data then you are going to need databases. We will always tend towards PostgresSQL as our database of choice but we have experience with a wide range of databases and we are always happy to work with whatever you have in place or want to use.

A cache is a fast temporary storage layer, such as Redis, that keeps frequently used data close to the application so it does not have to repeatedly fetch or compute it from a slower source like a database, API, or data warehouse. Caches are essential for improving performance and scalability in data systems, and we have extensive experience working with them to optimize data access and reduce latency.

In any data application you need to be able to input and output the data in a human friendly way. We build custom user interfaces and dashboards that allow you to interact with your data, monitor key metrics, and manage your operations without needing to understand the technical details of the data. Typically Javascript languages are used for this layer in data heavy apps.

The user experience is often the most important part of any data system. If the people who need to use the system cannot understand it or do not trust it then it will not be used and it will not have any impact. We design and build data systems with the user experience front of mind, ensuring that they are intuitive and reliable.

We write clean, maintainable code that powers our data systems and ensures they run smoothly. We use IDE's such as VSCode and we use GitHub for version control. We use Claude code and Codex to assist in coding using DDD, SDD and TDD methodologies. We write code in a range of languages including Python, JavaScript, TypeScript, SQL and more depending on the needs of the project.

An API — Application Programming Interface — is a defined way for one piece of software to communicate with another. In web apps, an API usually means a set of URLs/endpoints that let your frontend, backend, or another service request or change data. So the API acts as a controlled doorway between the user interface and the underlying system. There are lots of types of APIs such as REST, GraphQL, Websockets and Webhooks and it is possibly the most confusing part of data system design.

DevSecOps means building security into every stage of software delivery, rather than checking it at the end. Key aspects include secure coding, automated testing, dependency scanning, secrets management, infrastructure-as-code checks, container security, access control, logging, monitoring, and incident response. It combines developers, operations, and security teams around shared responsibility. Not easy to do, but essential.

Most data systems output data to the users which now means email, SMS, Slack, WhatsApp and more. All need integration. All need security. Good integration ensures users receive timely updates, confirmations, alerts, and support messages across the right channel. It should also protect privacy, respect notification preferences, handle opt-outs, and maintain audit trails for compliance and debugging.