One finance data & analytics platform on cloud with scalable architecture
We designed a modular, scalable cloud platform on AWS that grew from a single finance use case into one governed foundation for finance analytics.
About the client
Global pharmaceutical manufacturer operating across multiple business divisions and international markets.
The challenge
The client’s Finance division needed to establish a scalable enterprise data platform capable of supporting financial analytics, complex simulations, and future data-driven initiatives across multiple finance domains.
- Unknown final scope of data sources and consuming applications and projects at the outset
- A flexible architecture designed to scale beyond the first prioritized use case, EPIC, focused on foundational financial master data and supporting future analytics projects and applications
- Integration of heterogeneous financial systems with differing structures and refresh cycles
- Secure processing, storage, and consumption of sensitive financial data
- Support for multiple consumption patterns across analytical tools and project teams
- Standardization of ingestion, orchestration, and data-quality processes across the platform
The solution
UD4D helped design a scalable, high-level cloud-based architecture and address specific integration and data-consumption needs across projects.
- Design of a modular AWS-based architecture supporting data ingestion, processing, storage, and consumption
- Definition of integration, side-load, and consumption patterns tailored to individual Finance projects
- Security models across the full data lifecycle, with role-based access and separation of managed and self-service environments
- Orchestration patterns using Airflow and Matillion, with dependency management and cross-environment execution
- Redshift data layer structure enabling both governed and self-service analytics
- Alignment with governance and data-quality standards through Collibra and Collibra Data Quality
- Support for Dataiku-based modeling and Power BI reporting
Business impact
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19
data sources unified on one platform
The architecture grew from the initial EPIC use case to ingesting 19 financial data sources and supporting 8 analytical applications.
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4
levels of analytics enabled
The unified financial data layer supports descriptive, diagnostic, predictive, and prescriptive analytics on consistent data.
-
2
operating models on one platform
Sensitive financial data is processed securely and under governance across both managed and self-service environments.
-
3
core processes standardized
Standardized ingestion, orchestration, and data-quality processes accelerate onboarding of new Finance projects and speed delivery across the domain.
Frequently asked questions
What did the client’s Finance division need?
A scalable enterprise data platform capable of supporting financial analytics, complex simulations, and future data-driven initiatives across multiple finance domains.
How is the platform architected?
As a modular AWS architecture (S3, Redshift, Glue, IAM) covering data ingestion, processing, storage, and consumption. Orchestration runs on Airflow and Matillion, ingestion on the DIFW framework, modeling in Dataiku, and reporting in Power BI.
How does it support both governed and self-service analytics?
A Redshift data layer together with role-based security separates managed and self-service environments, so sensitive financial data stays governed while project teams keep flexible access. Governance and data quality are aligned through Collibra and Collibra Data Quality.
What did the platform deliver?
It scaled from the initial EPIC use case to 19 data sources and 8 analytical applications on one platform, enabled four levels of analytics (descriptive, diagnostic, predictive, prescriptive), and standardized ingestion, orchestration, and data-quality processes.