Affinity Federal Credit Union embraces Self-Service Business Intelligence
公司规模
Large Corporate
地区
- America
国家
- United States
产品
- AtScale
- Snowflake
- Excel
- Tableau
技术栈
- Self-Service BI
- Analytics Modernization
- Cloud Migration
实施规模
- Enterprise-wide Deployment
影响指标
- Productivity Improvements
- Digital Expertise
- Customer Satisfaction
技术
- 分析与建模 - 实时分析
- 平台即服务 (PaaS) - 数据管理平台
适用行业
- 金融与保险
适用功能
- 商业运营
- 销售与市场营销
用例
- 实时定位系统 (RTLS)
- 质量预测分析
服务
- 数据科学服务
- 系统集成
关于客户
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.
挑战
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.
解决方案
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.
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