Incorta Case Studies Fast, Flexible and Autonomous Data Science at Redstone Federal Credit Union

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	Fast, Flexible and Autonomous Data Science at Redstone Federal Credit Union Incorta

Fast, Flexible and Autonomous Data Science at Redstone Federal Credit Union

Incorta

Technology Category	Analytics & Modeling - Big Data Analytics Analytics & Modeling - Machine Learning
Applicable Industries	Cement Finance & Insurance
Use Cases	Autonomous Transport Systems
Services	Data Science Services System Integration
Challenge	Redstone Federal Credit Union, a financial institution with 1,001-5,000 employees, was facing a significant challenge in leveraging data to gain more visibility and control over banking operations. The credit union aimed to deliver more value to its members through data-driven insights. However, fragmented data spread across a myriad of systems and applications was a major obstacle. This fragmentation was holding back the credit union's Business Intelligence (BI) and data science initiatives, preventing them from making the progress they desired. The data science team was heavily reliant on the IT team, which was slowing down their ability to innovate with data. Read More
About Customer	Redstone Federal Credit Union is a financial institution with a workforce of 1,001-5,000 employees. The credit union is committed to leveraging data to gain more visibility and control over banking operations, with the ultimate goal of delivering more value to its members. The credit union's data science team leads its machine learning efforts and is tasked with organizing and joining complex data, building schemas, and creating new dashboards. The team was previously reliant on the IT team, which was slowing down their ability to innovate with data. Read More
Solution	Redstone Federal Credit Union deployed Incorta, a unified data and analytics platform, to overcome their data fragmentation challenge. Incorta was set up in a matter of days and was able to pull in 13 million records from Redstone's Fiserv core banking system in just 43 seconds. This platform served as a 'data hub' for Redstone's data science team, leading the credit union's machine learning efforts. With Incorta, data scientists could independently organize and join complex data, build schemas, and create new dashboards without burdening the IT team. The Incorta-powered data hub enabled Redstone's data scientists to build smarter predictive models and provide more timely, relevant, and useful data insights to teams across the organization. Incorta also facilitated cross-team collaboration by bringing everyone together on the same platform, making it easier for data scientists to partner with subject matter experts when investigating business questions and anomalies. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Big Data Analytics

Analytics & Modeling - Machine Learning

Applicable Industries

Cement

Finance & Insurance

Use Cases

Autonomous Transport Systems

Services

Data Science Services

System Integration

Challenge

Redstone Federal Credit Union, a financial institution with 1,001-5,000 employees, was facing a significant challenge in leveraging data to gain more visibility and control over banking operations. The credit union aimed to deliver more value to its members through data-driven insights. However, fragmented data spread across a myriad of systems and applications was a major obstacle. This fragmentation was holding back the credit union's Business Intelligence (BI) and data science initiatives, preventing them from making the progress they desired. The data science team was heavily reliant on the IT team, which was slowing down their ability to innovate with data.

About Customer

Redstone Federal Credit Union is a financial institution with a workforce of 1,001-5,000 employees. The credit union is committed to leveraging data to gain more visibility and control over banking operations, with the ultimate goal of delivering more value to its members. The credit union's data science team leads its machine learning efforts and is tasked with organizing and joining complex data, building schemas, and creating new dashboards. The team was previously reliant on the IT team, which was slowing down their ability to innovate with data.

Solution

Redstone Federal Credit Union deployed Incorta, a unified data and analytics platform, to overcome their data fragmentation challenge. Incorta was set up in a matter of days and was able to pull in 13 million records from Redstone's Fiserv core banking system in just 43 seconds. This platform served as a 'data hub' for Redstone's data science team, leading the credit union's machine learning efforts. With Incorta, data scientists could independently organize and join complex data, build schemas, and create new dashboards without burdening the IT team. The Incorta-powered data hub enabled Redstone's data scientists to build smarter predictive models and provide more timely, relevant, and useful data insights to teams across the organization. Incorta also facilitated cross-team collaboration by bringing everyone together on the same platform, making it easier for data scientists to partner with subject matter experts when investigating business questions and anomalies.

Impact #1	The deployment of Incorta has significantly improved Redstone Federal Credit Union's data science capabilities. The data science team can now move faster and innovate more freely with data as they no longer have to rely on the IT team. This has led to the creation of smarter predictive models and the provision of more timely, relevant, and useful data insights to teams across the organization. The unified data and analytics platform has also improved cross-team collaboration, making it easier for data scientists to partner with subject matter experts when investigating business questions and anomalies. Furthermore, the platform has empowered users to uncover new and unexpected insights to complex questions, such as the reasons for particular credit cards being inactive or a spike in fraud.

Impact #1

The deployment of Incorta has significantly improved Redstone Federal Credit Union's data science capabilities. The data science team can now move faster and innovate more freely with data as they no longer have to rely on the IT team. This has led to the creation of smarter predictive models and the provision of more timely, relevant, and useful data insights to teams across the organization. The unified data and analytics platform has also improved cross-team collaboration, making it easier for data scientists to partner with subject matter experts when investigating business questions and anomalies. Furthermore, the platform has empowered users to uncover new and unexpected insights to complex questions, such as the reasons for particular credit cards being inactive or a spike in fraud.

Benefit #1	Incorta was deployed in just a few days
Benefit #2	Incorta pulled in 13 million records from Redstone's Fiserv core banking system in 43 seconds
Benefit #3	Queries return results in sub-second response times

Benefit #1

Incorta was deployed in just a few days

Benefit #2

Incorta pulled in 13 million records from Redstone's Fiserv core banking system in 43 seconds

Benefit #3

Queries return results in sub-second response times

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Overview

Fast, Flexible and Autonomous Data Science at Redstone Federal Credit Union

Operational Impact

Quantitative Benefit