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Build

Data Foundation

One data foundation, documented, with costs under control.

  1. Assess
  2. Build
  3. Run

The problem

“Our data is scattered and our costs keep rising.”

Deliverables

  • One data model per domain, with shared metric definitions
  • BigQuery (Dataform) or Fabric (Lakehouse, Warehouse) data marts
  • Versioned, tested and documented transformations
  • Separate environments and a release process
  • Cost optimization: partitioning, clustering, queries

How it works

  1. Map

    Sources, usage, costs and key metrics.

  2. Model

    A target model per domain, validated with the business.

  3. Build

    Versioned transformations and first data marts in production.

  4. Optimize and hand over

    Cost review, documentation and training for your teams.

What comes next

Run

Monthly support to keep your platform running and evolving.

Case studies

Related case studies

  • Jewelry

    International jewelry house

    Running BI for an international jewelry house

    Context
    Reporting on SAP BusinessObjects and SQL Server to migrate to Power BI and Google Cloud for finance, omnichannel and supply, with thousands of users worldwide.
    Outcome
    4,000–5,000 self-service users worldwideAround 20 standardized report templates on certified data
    • Power BI
    • BigQuery
    • Microsoft Fabric
    • Migration
  • Healthcare / Medtech

    Medtech group

    Moving beyond Excel: a medtech group's first BI platform

    Context
    A medtech group with no BI platform: sales, marketing, finance and leadership ran the business from large Excel files and exports reworked by hand.
    Outcome
    130+ users across sales, marketing, finance and leadership-50% manual data handling
    • Power BI
    • CRM
    • Self-service
    • Automation

Contact

A solid foundation before anything else?

Let's talk about your sources, your usage and your bill.

Book a callStart with an assessment[email protected]