An overview of our services

We build and operate the data ecosystem

  • Cloud Data Platform Design (GCP): Design and implementation of 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 analytical data, and provide them in a structured manner.

  • Data & Project Structuring: Defining a clean structure for GCP projects, datasets and data scopes – ensuring transparency, maintainability and scalability.

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

  • Transformation Environment Setup: Setting up Dataform for versioned, traceable and testable data models – as the foundation for consistent analytics and BI applications.

  • Operation & Platform Readiness: Building a platform that can be operated stably, extended and further developed by internal teams – within a project or client model.

When is it worth adopting a new architecture?

Typical signs that action is needed at platform level:

  • Scalability reaches its limits: as usage increases, reporting becomes slow or unstable.

  • Unclear data landscape: Inconsistent data states, duplicate logic, lack of a ‘single source of truth’.

  • Governance gaps: Access, responsibilities and data provenance are not clearly defined.

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

  • Cloud complexity: The platform exists technically, but is difficult to maintain or barely scalable.

Our approach

We don’t build theoretical concepts, but operational infrastructures.

Platforms that work in everyday use: We don’t build theoretical blueprints, but operational analytics platforms that support reporting, advanced analytics and activation in equal measure.

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 business units can operate – whilst 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, high-performing and scalable in the long term.

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

What do you end up with?

  • Ready-to-use analytics platform: A configured Google Cloud environment with clearly structured data domains.

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

  • Transformation setup: Set-up Dataform environment for modelling and transformation.

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

  • Analytics & 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 the better fit? Our Google Cloud architectures are designed to support both traditional reporting and advanced analytics and AI applications (e.g. using BigQuery ML or Vertex AI).

Is the platform only suitable for BI, or also for AI? Our architectures are designed to support both traditional reporting and advanced analytics and AI applications.

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