The Challenge: A Data Infrastructure That Couldn’t Keep Pace
Managing data at the scale of one of Europe’s largest trade and tourism conglomerates is not a small problem. With over 380,000 employees, 15,000+ stores across 21 countries, and more than €100 billion in annual revenue, the volume of data generated across sales, inventory planning, and organizational operations is enormous — and growing.
For years, the business relied on SQL-based infrastructure to process and report on this data. But as the volume scaled, so did the costs and the constraints. Queries became slow. Cross-functional reporting required significant effort to reconcile data from multiple siloed systems — sales, planning, and operations each held their own version of the truth.
Incremental fixes were no longer enough. Patching the old system would only delay the inevitable. What the business needed was not a workaround. It needed a fresh start.
The Discovery: Bringing in IDS
IDS Consulting was brought in to do what the business had not yet been able to do on its own: design and deliver a modern data platform that matched the scale and ambition of the organization.
The mandate was clear — not to improve the existing architecture, but to replace it entirely. And critically: to do so without losing the one thing the client had already built over years of operation: deep institutional knowledge of their data — what it was, where it came from, and how it was used across the business.
The Solution: Building the Data Foundation on Snowflake
IDS designed and implemented a greenfield cloud data platform on Snowflake — built from the ground up, not layered on top of legacy systems. Starting fresh did not mean starting blind. The client’s institutional knowledge became the blueprint.
- A unified data model. Purpose-built to reflect how the business actually works — not a migration of old structures, but a complete redesign across sales, planning, and operations.
- Snowflake as the cloud backbone. Replacing costly SQL bottlenecks with Snowflake’s cloud-native processing, designed to handle massive and growing data volumes without degradation.
- Single source of truth. Consolidating data from multiple source systems into one unified layer, eliminating the reconciliation effort that consumed analyst time at every reporting cycle.
- Formalized data definitions. The institutional knowledge that existed informally — data lineage, source rules, consumption logic — was structured, documented, and made reusable.
The Battle: Designing for Scale Without a Playbook
Two challenges defined this engagement.
The first was the starting point itself. A greenfield project at this scale — spanning 21 countries, 15,000+ stores, and multiple business functions — meant there was no existing template to follow. Every data model decision, every integration pattern, every architectural choice had to be made deliberately and defensibly, from scratch.
The second was alignment. With data flowing from sales, planning, and organizational systems — each with its own history, format, and business logic — reaching a unified model required painstaking cross-functional coordination. The team had to translate years of informal knowledge into formal architecture while keeping delivery on track.
The Results: Quality Data, At Any Scale
- Faster cross-functional reporting. Queries that previously took hours now complete in minutes — freeing analysts to focus on insight, not waiting.
- Scalability unlocked. The Snowflake platform handles growing data volumes across the full retail network without performance degradation.
- Single source of truth. Sales, planning, and operational teams work from the same data, eliminating reconciliation conflicts and version disputes.
- Reduced infrastructure cost. Cloud-native scaling eliminates the over-provisioning that made on-premise SQL environments expensive to maintain.
- An ongoing foundation for growth. The platform is not just a solution to today’s problem — it is the architecture the business will grow into for years to come.