Introduction
Bucknell University is a highly-ranked private institution offering a blend of liberal arts and professional programs. As the university modernised key enterprise systems, it set out to build a scalable, cloud-based data warehouse. Bucknell chose WhereScape to accelerate development, automate repetitive tasks, and support a more agile, future-ready architecture.
Pre-WhereScape Challenges
- Rigid ERP ecosystem: Ellucian Banner’s ERP system included BI tools which operated as a “black box” making changes slow & difficult.
- Lack of agility: A small development team faced tight deadlines and needed faster turnaround than traditional ETL methods allowed.
- Platform instability: Performance issues and limited flexibility began affecting reporting reliability across departments.
- New system integrations: Adding cloud-based systems like Workday, Slate & Blackbaud CRM required major architectural redesign.
- Emerging data types: The university needed to support semi-structured and non-relational data beyond traditional warehouse models.
Why WhereScape?
Bucknell selected WhereScape after discovering data warehouse automation during its evaluation of ETL tools. WhereScape offered the maturity, speed, and automation capabilities required to eliminate tedious manual coding, generate documentation instantly, and enable agile data warehouse design: making it the best fit for a lean BI team transitioning to a modern, multi-system environment.
“We can build data models much faster than previously and much faster than using a traditional ETL tool.”
– Ken Flerlage, Business Intelligence Functional Architect, Bucknell University
The Solution
Cloud-Ready Architecture
Bucknell deployed a cloud-based data warehouse on AWS RDS using SQL Server, supported by MongoDB Atlas for semi-structured data, enabling flexible storage and fast reporting across new enterprise systems.
Automated Data Warehouse Development
WhereScape RED automated schema generation, ELT code creation, documentation, and data lineage tracking, reducing manual work and accelerating delivery timelines.
Seamless System Integration
The architecture brought together data from Banner, Workday, Blackbaud CRM, Slate, and additional sources, enabling unified institutional reporting.
Agile Validation and Testing
Through traceable lineage and click-through impact analysis, the BI team quickly validated discrepancies and improved accuracy during development.
Results
🚀 Faster Development Cycles
- Delivered student module in half the time of traditional ETL.
- Automated redundant tasks to streamline workflows.
- Enabled rapid prototyping for new data models.
🚀 Improved Data Governance
- Full lineage visibility with track-forward and track-back features.
- Accelerated impact analysis for safer iterative changes.
- Generated technical and business documentation instantly.
🚀 Scalable Cloud Performance
- Leveraged AWS RDS and MongoDB Atlas for flexible data storage.
- Supported structured and semi-structured data sources.
- Enabled smooth integration with reporting tools like Cognos and Tableau.
🚀 Exceptional Support
- Fast response times with knowledgeable product experts.
- Access to best-practice guidance for complex development questions.
- Personalised assistance from a specialist team.
“My support tickets are always answered very quickly and they truly listen to my suggestions. Their support team knows the product inside and out.”
– Ken Flerlage, Business Intelligence Functional Architect, Bucknell University
Architectural Evolution
Bucknell’s shift from a monolithic ERP-driven reporting ecosystem to a heterogeneous, best-of-breed model required a modern architecture capable of handling multiple cloud platforms. This included consolidating data from Workday, Banner, Slate, and Blackbaud CRM, ensuring reporting consistency across administrative and academic functions.
Automation as a Strategic Advantage
The university’s BI team emphasised the importance of eliminating manual SQL scripting and repetitive development tasks. Automation allowed the team to focus on business-level logic, data modelling, and stakeholder needs rather than low-level code generation.
Agile Data Warehouse Design
WhereScape’s alignment with agile methodologies supported Bucknell’s shift toward iterative development. Instead of lengthy design cycles, the team could adjust models rapidly as new requirements emerged. This approach was especially valuable during large-scale system migrations.
Recommended Practices
Bucknell encourages organisations adopting data warehouse automation to embrace a new mindset. Instead of treating automation as a direct ETL replacement, the shift must reflect agile, iterative design principles; supported by resources such as Agile Data Warehouse Design by Corr and Stagnitto, which the team found foundational in guiding their transition.
