Our services at a glance

We build and operate the data ecosystem

  • Cloud Data Platform Design (GCP): Design and build modern analytics platforms on Google Cloud – tailored to your IT, security and governance requirements.

  • Cloud Data Warehouse & Lakehouse (BigQuery): Design and implementation of scalable data storage concepts that clearly separate raw data, processed data and business-relevant analysis data and provide them in a structured manner.

  • Data & Project Structuring: Definition of a clean structure for GCP projects, datasets and data areas – for transparency, maintainability and scalability.

  • Security, governance & access control: Implementation of security and governance concepts directly at the platform level: roles, access models, data classification and auditability.

  • Transformation environment setup: Setting up Dataform for versioned, traceable and testable data models – as a basis for consistent analytics and BI applications.

  • Operation & platform readiness: Building a platform that can be operated stably, expanded and further developed by internal teams – in a project or mandate model.

When is a new architecture worthwhile?

Typical signs that action is needed at platform level:

  • Scalability reaches its limits: Reports become slow or unstable as usage increases.

  • Unclear data landscape: Different data statuses, duplicate logic, lack of a "single source of truth".

  • Governance gaps: Access, responsibilities and data origin are not clearly regulated.

  • Analytics and AI projects fail at the grassroots level: Advanced analytics or AI are planned, but the data platform is not prepared.

  • Cloud complexity: The platform is technically available, but difficult to maintain or expand.

Our approach

We don't build theoretical concepts, we build operational infrastructures.

 

Platforms that work in everyday life: We don't build theoretical target visions, but operational analytics platforms that equally support reporting, advanced analytics and activation.

Governance & security by design: A good platform enables self-service without losing control. We implement governance, access models and security zones in such a way that specialist departments can work while sensitive data remains protected.

For Swiss companies, we consistently take data residency (CH/EU) into account.

Focus on proven platforms: We deliberately focus on Google Cloud with BigQuery and Dataform. This reduces complexity, ensures quality and guarantees that your analytics platform remains maintainable, performant and expandable in the long term.

Enablement & handover: We document architecture, data structures and operating logic and empower your teams to further develop the platform independently – both technically and organisationally.

What do you end up with?

  • Operational analytics platform: Configured Google Cloud environment with clearly structured data areas.

  • Architecture blueprint: Visualised data flows, platform components and integration points.

  • Transformation setup: Configured Dataform environment for modelling and transformation.

  • Governance and access concept: Documented roles, access models and responsibilities.

  • Analytics and AI readiness: A platform that reliably supports reporting, advanced analytics and AI use cases.

Frequently asked questions (FAQ)

Google Cloud or Microsoft Fabric – which is better suited? Our Google Cloud architectures are designed to support both classic reporting and advanced analytics and AI applications (e.g. with BigQuery ML or Vertex AI).

Is the platform only suitable for BI or also for AI? Our architectures are designed to support classic reporting as well as advanced analytics and AI applications.

Can specialist departments work with the data themselves? Yes – via clearly structured data models, views and controlled self-service access, without compromising governance or security.