Data Warehousing & Analytics
A warehouse and model that answer the questions the business actually asks, at a cost you can predict.
Read moreGoogle Cloud design and delivery, particularly where data, analytics and machine learning lead the decision.
Google Cloud tends to win on data. BigQuery remains the most approachable serverless warehouse available, GKE is the most mature managed Kubernetes, and Vertex AI puts model work close to where the data already sits. For analytics-heavy organisations, that combination is often decisive.
We design and build GCP environments with the same discipline we apply anywhere else: clear project and folder structure, IAM that follows least privilege, and Terraform as the source of truth.
BigQuery, Dataflow and Pub/Sub arranged around the questions your business actually asks.
GKE Autopilot or standard clusters, configured with sensible defaults rather than every feature enabled.
Folders, projects and IAM that keep environments and teams properly separated.
Vertex AI pipelines when there is a real model to serve, and nothing more when there is not.
We establish what the workload needs and whether GCP is genuinely the right home for it.
Organisation hierarchy, networking, IAM and billing structure set up before any workload lands.
The workload is built, instrumented and load-checked against realistic data volumes.
Documentation, cost baselines and a handover session for the team who will run it.
Sometimes, for a specific workload such as analytics. Running two providers has a real operational cost, so the benefit needs to be concrete before we recommend it.
Yes — modelling, partitioning, cost control and connecting it to the reporting tools your team already uses.
We can build the surrounding infrastructure, pipelines and evaluation. We will be candid about whether a model is the right answer at all.
A warehouse and model that answer the questions the business actually asks, at a cost you can predict.
Read moreProduction Kubernetes with sane defaults, guardrails and documentation — or honest advice that you do not need it.
Read moreInfrastructure, pipelines and evaluation for AI systems — including telling you when you do not need one.
Read moreWe will tell you what we would do, roughly what it costs, and whether it is worth doing yet.