Selected engagements

What was broken, and what replaced it.

Written out rather than summarised into a logo wall, and anonymised by sector and size, because the confidentiality that protects these clients would protect you too. Where an outcome is not published, it is because nothing exists that would let you check it, which is a better answer than a number that sounds good.

  • Retail

    Foundation then Activation then Acceleration alongside Stewardship

    Store revenue, executive questions and forecasting on one set of definitions

    A retailer with Microsoft Fabric already in production, semantic models over Direct Lake and store revenue streaming in, who wanted forecasting, Copilot questions and anomaly detection on top of it.

    • Microsoft Fabric
    • Power BI semantic models
    • Direct Lake
    • Copilot in Power BI
    • Fabric AI Functions
    • Activator

  • Industrial manufacturing

    Foundation then Activation then Acceleration

    Governed reporting across a production network

    An industrial manufacturer reporting across a production network of sites, each with its own view of what was running.

    • Microsoft Fabric
    • OneLake
    • OneLake Security
    • Direct Lake
    • Spark
    • MES
    • OPC UA
    • Power BI
    • DAX
    • Azure Key Vault
    • Purview
    • Azure DevOps

  • Hospitality and real estate

    Foundation then Activation

    A CFO cockpit over a group that closed its books separately

    A holding group across hospitality and real estate, with entities that each closed their own books and a CFO who had to answer for all of them.

    • Microsoft Fabric
    • OneLake
    • Direct Lake
    • Databricks Mirrored Catalog
    • Fabric Data Factory
    • Power BI
    • DAX
    • Calculation groups
    • Row-level security
    • Azure DevOps
    • Azure Key Vault
    • Purview

  • Multi-brand retail

    Foundation then Activation

    One governed model across a multi-brand retail group

    A retail group running several brands, each with its own systems, its own reporting habits and its own answer to what a margin is.

    • Microsoft Fabric
    • Direct Lake
    • Databricks
    • Eventstream
    • KQL Database
    • Power BI
    • DAX
    • SAP
    • Salesforce
    • Azure DevOps

  • Omnichannel e-commerce

    Foundation then Activation

    Finance reporting that keeps up with the day

    An omnichannel retailer whose finance leadership was steering on yesterday’s numbers in a business that changes within the day.

    • Microsoft Fabric
    • OneLake
    • Direct Lake
    • Fabric Data Factory
    • Eventstream
    • Power BI
    • DAX
    • REST APIs
    • ERP integration

  • Internet and IT

    One set of subscription metrics for finance, product and customer teams

    An internet company of 50 to 250 people with subscription revenue, whose finance, product and customer teams each kept their own spreadsheets.

    • Power BI
    • DAX
    • SQL
    • Dataflows
    • Azure Data Factory
    • Semantic modelling

  • Internet and IT

    Fragmented customer data, moved to one warehouse that watches churn

    An internet company of 250 to 500 people with several business units, each holding its own copy of the customer data.

    • Snowflake
    • Databricks
    • Azure Data Factory
    • Power BI
    • SQL

  • Telecommunications

    Finance and sales reporting, moved off legacy SQL and Excel

    A telecommunications company of 250 to 500 people whose finance and sales reporting had been built on legacy SQL and Excel, report by report.

    • Power BI
    • DAX
    • SQL
    • Azure Data Factory
    • Azure Synapse

  • Mechanical engineering

    A stalled Power BI rollout, taken over and brought back on track

    A mechanical engineering company of 50 to 250 people, with a Power BI implementation that had been started and then stalled.

    • Power BI
    • DAX
    • Semantic modelling
    • SQL
    • Dataflows
    • Data governance

  • Transport and logistics

    Supply-chain data, out of many Excel files and into one model

    A transport and logistics company of 50 to 250 people whose shipment and warehouse data lived in many separate Excel files.

    • Power BI
    • DAX
    • SQL
    • Snowflake

  • Retail

    A Fabric foundation for a retailer’s finance and sales

    A mid-size retailer of 50 to 250 people that needed reporting that finance and sales could both trust, built on Microsoft Fabric.

    • Microsoft Fabric
    • OneLake
    • Power BI
    • DAX
    • SQL
    • Dataflows Gen2

  • Several sectors, mid-size

    Manual Excel, replaced by governed models, one engagement at a time

    Several organisations of 50 to 250 people, each with a contained reporting problem in one department: finance, HR or production.

    • Power BI
    • DAX
    • SQL
    • Azure Synapse
    • Azure Data Factory
    • Dataflows

Seven of these engagements predate the current packages, so they name no tier. The detail behind any of them is available on request under NDA.

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