AtScale Case Studies Affinity Federal Credit Union embraces Self-Service Business Intelligence

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	Affinity Federal Credit Union embraces Self-Service Business Intelligence AtScale

Affinity Federal Credit Union embraces Self-Service Business Intelligence

AtScale

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
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. Read More
About 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. Read More
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. Read More Log in to view content
Contents

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

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.

About 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.

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.

Impact #1	By applying AtScale’s semantic layer, AFCU gained the ability to manage data models, calculations, dimension definitions, access controls, and governance in a single location — all integrated with business tools like Excel and Tableau.
Impact #2	Improved business outcomes are a natural consequence of applying a semantic layer, and the organization’s citizen data scientists benefit from being able to do their jobs more effectively with self-service BI.
Impact #3	With a semantic layer, AFCU is able to use business tools the team is already comfortable with to access deeper and more relevant insights, all while retaining autonomy and building up knowledge capital for the organization.

Impact #1

By applying AtScale’s semantic layer, AFCU gained the ability to manage data models, calculations, dimension definitions, access controls, and governance in a single location — all integrated with business tools like Excel and Tableau.

Impact #2

Improved business outcomes are a natural consequence of applying a semantic layer, and the organization’s citizen data scientists benefit from being able to do their jobs more effectively with self-service BI.

Impact #3

With a semantic layer, AFCU is able to use business tools the team is already comfortable with to access deeper and more relevant insights, all while retaining autonomy and building up knowledge capital for the organization.

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Overview

Affinity Federal Credit Union embraces Self-Service Business Intelligence

Operational Impact