Saint-Maclou accelerates analytics across 132 stores with Fivetran + dbt

“Fivetran gives us the flexibility to quickly integrate new data sources, so our team can focus on transforming and modeling data with dbt instead of maintaining pipelines. That allows us to support initiatives such as sales forecasting and experimenting with new AI and data science use cases.”
— Salmane Khamlichi, Head of Data, Saint-Maclou

Saint-Maclou is one of France's leading flooring retailers, operating 132 stores supported by a centralized logistics network. With more than 1,400 employees, the company depends on timely, trusted data across sales, inventory, logistics, finance, marketing, and installation services to run its business.

As demand for data grew, the company's legacy ETL architecture — spread across 10 on-premises ETL tools — became a bottleneck. Business teams couldn't access new data quickly enough to support operational and strategic decision-making, while engineers spent more time building and maintaining custom pipelines than delivering insights. Onboarding new data sources often took days or weeks, delaying analytics projects, increasing operational costs, and slowing the business's ability to respond to changing priorities.

At the same time, Saint-Maclou was modernizing its technology stack — including the rollout of Salesforce as its new CRM — and deploying Snowflake as its cloud data platform. As part of this transformation, the company needed a reliable, scalable, and standardized way to continuously synchronize operational data, accelerate analytics, and build a foundation for new AI initiatives.

Automating data movement and transformation with Fivetran and dbt

Saint-Maclou selected Fivetran for its native Snowflake integration, proven reliability during a proof of concept, and ability to replicate large SQL Server databases alongside a broad range of business applications. As the company rolled out Salesforce as its new CRM, it also selected Fivetran to synchronize Salesforce data into Snowflake, choosing it over native integration alternatives based on its reliability and existing partnership.

Today, Fivetran synchronizes data from operational and cloud platforms with nearly 150 managed connectors, including Microsoft AX ERP, logistics systems, sales and inventory platforms, Google Ads, Salesforce, and other business applications into Snowflake. The platform ingests approximately 23 million rows each month and now accounts for roughly 70% of all data stored in Snowflake, creating a centralized foundation for analytics across the organization.

Once data lands in Snowflake, Saint-Maclou’s data team uses dbt Core to transform raw operational data into analytics-ready data sets for business users. With data ingestion automated, engineers can focus on modeling business logic and transforming raw data into trusted, analytics-ready data sets instead of building and maintaining pipelines.

Together, Fivetran and dbt allow engineers to spend less time managing pipelines and more time delivering trusted analytics. The result is a scalable data foundation that accelerates new analytics initiatives while supporting future AI use cases.

"By automating data movement and giving our team more time to focus on transformation and modeling, we're able to experiment with new data science and AI use cases at a much lower cost. That allows us to innovate faster while delivering more value to the business."
— Salmane Khamlichi, Head of Data, Saint-Maclou

Turning data into faster business decisions

With automated data movement and a centralized cloud platform, Saint-Maclou can deliver analytics faster, support business teams more effectively, and scale new data initiatives:

• Accelerated analytics delivery: New data sources that once took days or weeks to onboard can now be integrated in hours, keeping analytics projects within the same sprint and getting insights to business teams faster.
• Higher-value engineering work: With Fivetran automating data ingestion, engineers can focus on transforming and modeling data with dbt Core instead of maintaining pipelines, freeing them to support sales forecasting and AI use cases such as image analysis, automated product descriptions, and document analysis.
• Reliable, near real-time data: Continuously refreshed KPIs give sales, logistics, finance, and marketing teams trusted data for faster decisions, while automated schema management prevents source changes from disrupting reporting.
• A centralized, trusted data foundation: Operational data from approximately 15 business systems is centralized in Snowflake, creating a single source of truth that improves cross-functional collaboration and ensures teams work from consistent business metrics.‍
• Greater operational visibility and cost control: Fivetran provides visibility into data consumption, helping Saint-Maclou monitor usage and control the cost of scaling its data platform and consolidate 10 legacy on-premises ETL tools into a single automated enterprise platform.

Saint-Maclou’s Fivetran and dbt data foundation has strengthened collaboration between the data team and business functions — including marketing, sales, and logistics — allowing new analytical use cases to reach the business faster. Building on its modern data foundation, the company is expanding its use of Snowflake Cortex for image analysis, automated product descriptions, document analysis, and sales forecasting. With trusted, continuously synchronized data readily available, engineers can focus on developing new AI-powered capabilities instead of managing data pipelines.

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