A Modern Data Platform on Snowflake, Azure Data Factory & Power BI

Note: Client details are anonymised. Figures are representative of a typical Technaptix data-platform engagement.

The challenge

A fast-growing retail and distribution enterprise ran on multiple systems — an ERP, a CRM, and an ever-growing sprawl of spreadsheets. Every team had its own numbers, and no two reports agreed. Analysts spent most of their week manually pulling and reconciling data instead of analysing it. Leadership couldn't trust a single dashboard, and any talk of AI or forecasting was premature — the data simply wasn't ready.

The approach

We built a modern data platform using a proven reference architecture, following the same pattern we describe in our Snowflake + Azure Data Factory guide:

• Ingestion with Azure Data Factory — reliable, scheduled pipelines pulling from the ERP, CRM, databases and key spreadsheets, with transformations and monitoring built in.
• Snowflake as the source of truth — all data landed in one governed, elastic cloud warehouse with consistent definitions and role-based access.
• Power BI for self-serve analytics — governed dashboards and AI-assisted reporting built directly on Snowflake, so every team reported from the same numbers.
• Conversational analytics on top — we layered Intellyca over the platform so business users could ask questions in plain language and get instant answers and forecasts.

The results

• One governed source of truth — conflicting spreadsheets replaced by a single, trusted Snowflake platform.
• 90% less manual data prep — analysts shifted from reconciling data to analysing it.
• Real-time, self-serve dashboards — leaders and teams answer their own questions in Power BI without waiting on reports.
• AI-ready foundation — with clean, current data in place, forecasting and conversational analytics became straightforward to add.

Why it worked

The win came from fixing the foundation first. Rather than bolting AI onto fragmented data, we built a governed platform — ADF for movement, Snowflake for storage, Power BI and Intellyca for consumption — so every downstream capability could trust its inputs. It's the same principle we apply across every AI in analytics and AI in ERP engagement: get the data right, and the intelligence pays off.

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