PROVEN IN DATA-AS-A-SERVICE

Real Systems, Real Results

While hospitality proves the model works on the brand and marketing side, the Data Engine side is already proven too — through hands-on, production experience turning messy ERP and business data into dashboards leadership actually uses.

That experience includes:

• Extracting and analysing sales, inventory and finance data directly from SAP ERP, building Power BI dashboards that became the shared reference point finance, sales and operations all worked from
• Designing and automating Python and SQL ETL pipelines on AWS (Glue, Spark, Airflow), cutting data ingestion and processing time by up to 40%
• Building Azure Data Factory pipelines handling 200,000+ SKUs, giving teams same-day visibility instead of week-old snapshots
• Replacing manual spreadsheet reporting with live Power BI and Tableau dashboards, cutting manual reporting effort by up to 60%
• Building real-time Python/SQL monitoring that improved SLA tracking accuracy by 50%
• Running NLP sentiment analysis on customer complaints to surface hidden patterns, contributing to a 15% lift in customer satisfaction
• Applying customer segmentation and behavioural analytics that improved marketing campaign efficiency by 25% — the direct bridge to the Growth Studio side of the business
• Building a working AI agent (LangChain) that automatically detects and fixes data-quality issues in sales/inventory files — a live example of the “AI-Augmented Analytics” flagship service, not a concept slide. The same approach extends to connecting an AI agent directly to a client’s systems — ERPs like SAP or Dynamics 365 Business Central included — so leadership can query the live database in plain English instead of waiting on a reportThis is also currently active: ongoing multi-client data-as-a-service consulting work — pulling data together across systems, building dashboards, and flagging trends clients wouldn’t catch from a single report — is exactly the delivery model this business is built on.