Affinity Federal Credit Union embraces Self-Service Business Intelligence
Company Size
1,000+
Region
- America
Country
- United States
Product
- AtScale
- Snowflake
- Excel
- Tableau
Tech Stack
- Self-Service BI
- Analytics Modernization
- Cloud Migration
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Customer Satisfaction
- Digital Expertise
- Productivity Improvements
Technology Category
- Analytics & Modeling - Real Time Analytics
- Application Infrastructure & Middleware - Data Exchange & Integration
- Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries
- Finance & Insurance
Applicable Functions
- Business Operation
- Sales & Marketing
Use Cases
- Predictive Quality Analytics
- Real-Time Location System (RTLS)
Services
- Data Science Services
- System Integration
About The Customer
Affinity Federal Credit Union (AFCU) is a large member-owned credit union that is in the top 2% of credit unions by asset size. The credit union prides itself on the ability to leverage newer technologies before much larger banks. AFCU is continually looking for opportunities to better leverage their data assets to improve service to their more than 185,000 members. They have a forward-looking data team that is always on the lookout for analytics governance options to enable broader self-service reporting across the organization.
The Challenge
Affinity Federal Credit Union (AFCU), a large member-owned credit union, was looking for opportunities to better leverage their data assets to improve service to their more than 185,000 members. They had been relying on legacy analytics infrastructure tools like ModelMax or Dundas BI, which required too much manual effort and slowed down decision-making. AFCU had been partnered with a Credit Union Service Organization (CUSO) that provided analytics-as-a-service, but this approach was slow and uncontrollable, often getting in the way of decision making and making it difficult to grow internal understanding of data. AFCU realized they couldn’t remain reliant on an outsourced analytics team and legacy processes to unearth insights from their data. It was time to transition to a modern, self-service BI program to allow faster, data-backed decision-making at scale.
The Solution
AFCU saw the importance of a semantic layer to establish analytics governance policies while establishing the level of flexibility needed to scale self-service BI. A semantic layer would allow for unified data access across all stakeholders in their business, technical and otherwise. AtScale was chosen as an independent semantic layer that enabled open connection to different BI platforms and different cloud services. This approach expanded access to data for both seasoned data scientists and to non-technical business users. By expanding data science programs, AFCU was able to incorporate advanced prescriptive and predictive analytics to their business, powering growth and smart decision-making. Building out the right semantic layer strategy was important to enabling outcome-based decision-making and gaining leverage from a treasure trove of customer and financial data. The AFCU team was able to leverage a flexible modeling environment to build views of raw data that addressed a wider range of business needs. The ability to quickly create new views of data, without relying on complex ETL, enabled the team to more rapidly iterate analytics.
Operational Impact
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