Cloud & platforms
- Microsoft Azure
- Microsoft Fabric
- AWS
- Google Cloud
- Databricks
- Snowflake
TECHNOLOGIES
Work with what you have—or what comes next.
We design, build, migrate and operate data and AI solutions across leading cloud, platform, engineering and analytics technologies.
CORE PLATFORMS
Technology expertise across the modern data stack.
Our recommendations are vendor-neutral and based on your requirements, existing estate, capability and total cost.
Cloud and data platform
Microsoft Azure & Fabric
Unified data engineering, analytics, AI and business intelligence across the Microsoft ecosystem.
↗Cloud and data platform
Amazon Web Services
Secure, scalable data platforms using AWS storage, integration, analytics and AI services.
↗Cloud and data platform
Google Cloud
Cloud-native analytics and AI using BigQuery, Dataflow, Dataplex and Vertex AI.
↗Lakehouse and AI platform
Databricks
A governed lakehouse for data engineering, analytics, machine learning and generative AI.
↗Cloud data platform
Snowflake
A scalable cloud data platform for governed sharing, analytics, applications and AI workloads.
↗Analytics engineering
dbt
Version-controlled transformation, testing and documentation for reliable analytics engineering.
↗Business intelligence
Microsoft Power BI
Enterprise reporting, governed semantic models and self-service analytics in the Microsoft ecosystem.
↗Business intelligence
Tableau
Visual analytics and governed self-service reporting for business teams and analytical users.
↗WIDER ECOSYSTEM
Tools selected to fit the architecture.
Engineering & integration
- dbt
- Airflow
- Kafka
- Fivetran
- Airbyte
- Azure Data Factory
Analytics & AI
- Power BI
- Tableau
- Looker
- MLflow
- Azure AI
- Vertex AI
Delivery & operations
- GitHub
- Azure DevOps
- Terraform
- Kubernetes
- Docker
- Monte Carlo
TECHNOLOGY SELECTION
Choose for fit, not fashion.
Workload fit
Data volumes, latency, integration, analytics and AI requirements.
Governance & security
Identity, access, privacy, lineage, residency and control obligations.
Team capability
Existing skills, delivery model, support capacity and learning curve.
Total cost
Licensing, consumption, engineering effort, operations and change cost.
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