The challenge
Reporting across sales, finance and procurement ran on an ageing warehouse fed by hand-written SQL. Loads were fragile and hard to maintain, each function saw a different version of the numbers, and trust in the data suffered as a result.
The company needed more than an upgrade: a strategy and target architecture that would carry its growing data and analytical needs for years, and a partner able to implement it end to end.
How we went about it
- 1
Strategy workshops
Workshops with key stakeholders across the functions defined the roadmap, strategy and target architecture for current and future data-engineering and analytical needs.
- 2
Warehouse on Snowflake
We built a high-performance data warehouse on Snowflake Cloud, with data models designed for both operational reporting and governed self-service.
- 3
Industrialised integration
Unmanageable free-hand SQL was migrated into automated, easily maintained data-load jobs in SAP Data Services.
- 4
BI layer and hand-over
SAP BusinessObjects, SAP Analytics Cloud and Power BI were connected to the governed models, and end users were enabled for self-service under proper data governance.
What we delivered
- Data strategy, roadmap and target architecture agreed with stakeholders.
- Snowflake data warehouse with operational and self-service data models.
- Automated, monitored load jobs replacing free-hand SQL.
- BI content across SAP BusinessObjects, SAP Analytics Cloud and Power BI.
Outcomes
What changed for the client
- Faster delivery of information and greater trust in the data.
- Data from every application, function and process available in a single view.
- End users enabled for self-service under proper data governance.
- A platform that supports ever-growing data and analytical needs.