WithSecure is a multinational SaaS company whose business naturally depends on trust. Its partners and customers rely on WithSecure to safeguard digital environments, and internally that same high standard applies to the company’s data operations. WithSecure’s data needs to be safe, reliable, understandable and ready when people need it.
WithSecure already had the ingredients for modern data work: business-critical source systems, data scientists, engineers, existing analytics assets and a clear ambition to build a stronger foundation. Reports, dashboards and pipelines supported daily work, but the foundation behind them needed to become easier to scale, govern and develop further.
The goal was to build a Databricks-based platform that could support analytics, dashboards, data science and next ML (machine learning) and AI use cases. WithSecure also wanted to strengthen its own data platform capabilities, so knowledge transfer, documentation and working practices were part of the work from the start.
Recordly joined WithSecure to design and implement the new data platform from scratch.
What Recordly built
The main challenge was connecting WithSecure’s data operations building blocks into a platform that could serve the whole company more consistently.
Recordly designed the data and analytics platform architecture and implemented Databricks as the core environment.
The platform brings WithSecure’s key data into one shared environment, so it can be used more easily for reporting, dashboards and data science work.
The work started with the platform foundation: how data is organized, who can access what, how environments are separated, how the setup is monitored, and how costs are followed. These choices were important because they affect how easy the platform is to use, maintain and extend later.
Recordly then implemented the Databricks environment, built the data ingestion and pipeline framework, migrated existing pipelines, reports and dashboards, and created new dashboards for selected business cases. The platform was built to support six business areas.
The team also created an MLOps foundation with MLflow and CI/CD, so WithSecure could start building more repeatable ways of developing ML use cases.
What changed
WithSecure now has a shared Databricks platform for analytics, ML and AI.
WithSecure’s key data can now be brought into one environment, shaped through common pipeline practices and fully utilized for reporting, dashboards and advanced analytics.
The project also reduced the burden of future development. New sources and use cases can follow the platform patterns created during the implementation. Moreover, cost governance, monitoring, access management and documentation are built into the setup.
For WithSecure, this means a complete data platform that can support current reporting needs and future AI ambitions with the same foundation.
What WithSecure said
“Recordly built us a Databricks foundation we can operate and build on. Governance, cost controls, infra-as-code and monitoring were designed to our specific needs from the start, not bolted on later.
Recordly's depth of Databricks expertise was a real value in the project. We could spar on design decisions and pressure-test our thinking against best practice, so the foundation fits WithSecure's actual requirements rather than a generic template.
Just as importantly, they worked alongside us as part of our team, so we came out of the project able to run and extend the platform ourselves. That combination is what made it a real platform for us, not just a delivery.”
— Markus Koponen, Head of Data Foundation,
WithSecure
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