TechnologyBusiness Intelligence

How SD Worx Uses Snowflake to Deliver Real-Time HR Analytics at Scale

SD Worx is a leading European HR, payroll, and workforce management solutions provider serving approximately 105,000 customers and 6 million employees across Europe. The company deployed Snowflake’s AI Data Cloud to replace a fragmented stack of disconnected HR tools, creating a single source of truth for workforce analytics. The result is a unified platform that gives customers from SMEs to global enterprises daily insight into wage costs, absenteeism, and compliance — while generating a new consultancy revenue stream for SD Worx itself.

Outcomes

650,000Employees supported by SD Worx insights
7,000Customers served with actionable HR data

Tools & Technologies

1MP
Microsoft Power BI
Business intelligence tool by Microsoft for interactive dashboards and self-service data visualization.
2S
Snowflake
Cloud data warehouse by Snowflake for storing, querying, and sharing structured and semi-structured data.
3SC
Snowflake Cortex AI
Built-in AI and ML capabilities within the Snowflake Data Cloud

AI Categories

Challenge

SD Worx customers were managing HR, payroll, and financial data across multiple disconnected tools, forcing finance and HR teams to manually extract and reconcile information before they could identify trends or act on workforce issues.

Solution

SD Worx deployed Snowflake’s AI Data Cloud on Azure as a unified data warehouse, using DBT and Azure Data Factory for ingestion and Power BI for embedded dashboards, with an Insights Cloud tier giving enterprise clients direct Snowflake access for self-serve analytics.

Full Story

SD Worx was founded in 1945 and has grown into one of Europe’s largest HR and payroll providers, processing workforce data for roughly 6 million employees across 105,000 client organizations. At that scale, the quality of analytics infrastructure directly determines how well customers can manage their people — and how competitive SD Worx’s platform remains.

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Source

SNOWFLAKE
May 2026
Original case study

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