A leading global provider of scientific instrumentation, consumables and software services needed to transform fragmented enterprise data into a trusted foundation for analytics and business decision-making. With more than 80 ERP systems and a wide range of third-party data sources, critical information was distributed across disconnected environments. This made it difficult to create a consistent enterprise view of spend, supply chain risk, finance, sustainability and supplier diversity.
The organization needed an enterprise data platform that could democratize access to data, standardize engineering practices and support scalable analytics across business functions.
Persistent partnered with the organization to co-engineer a cloud-native Enterprise Data Platform on AWS and Databricks.
When Fragmented Data Limits Enterprise Visibility
The client’s digital platforms were central to how customers discovered products, accessed content and engaged with services worldwide. While the platform, with more than 80 ERP systems, including SAP, Microsoft Dynamics NAV and Syspro remained functional, several factors were limiting its ability to scale efficiently:
- Multiple third-party systems contributing to a fragmented data landscape
- Data silos that limited access to trusted enterprise information
- Lack of a consolidated layer for harmonized analytics
- Need to create and manage reference data sets and metadata
- Growing demand for analytics across spend, supply chain risk, finance and sustainability
How Persistent Built a Cloud-Native Enterprise Data Platform
Persistent co-engineered an Enterprise Data Platform on AWS and Databricks to consolidate enterprise data and support repeatable analytics delivery. At the core of this strategy was a scalable optimization model capable of driving continuous improvement while focusing on:
- A common data engineering framework using Databricks notebooks for ETL and ELT workloads
- Reusable patterns designed to reduce Python coding effort
- Engineering best practices and CI/CD enablement
- An OutSystems-based reference data management solution
- Data engineering support for multiple business use cases, including spend analytics, supply chain risk analysis and finance
Standardizing Data Engineering for Faster Delivery
By establishing reusable frameworks and common engineering practices, Persistent helped the organization reduce variability across projects and accelerate the onboarding of new data sources.
The standardized platform enabled teams to onboard ERP systems faster, apply a common framework across projects, simplify ETL and ELT development, improve consistency in data processing and support repeatable delivery across enterprise use cases.
Delivering Enterprise-Wide Data Availability
The Enterprise Data Platform improved access to harmonized data across critical business functions, providing meaningful gains across delivery performance and platform governance.
- 80+ ERP systems connected to the Enterprise Data Platform
- 1,000+ source tables onboarded
- Faster onboarding of new ERP systems into the platform
- Standardized data engineering framework used across projects
- 80% spend coverage targeted through ERP onboarding by Q4 2023
- Data made available for spend, sustainability, supplier diversity and finance analytics
- Improved visibility into supply chain risk and financial information
From Disconnected Systems to Trusted Enterprise Data
Today, the organization has a scalable Enterprise Data Platform that connects data from ERP and third-party systems, supports harmonized analytics and enables faster access to business-critical information.
What began as an effort to address data silos evolved into a standardized data foundation for spend analytics, supply chain risk, sustainability, supplier diversity and finance.
Persistent helped transform fragmented enterprise data into a platform designed for enterprise-wide insight and future growth.
