This Guidance shows how credit unions can securely replicate and transform their Centralized Online Real-time Environment (core) banking data on AWS, unlocking actionable insights into key performance indicators such as new, lost, and returning members, deposit and loan growth, debit card usage, account openings, mortgage portfolios, member demographics, and bill pay adoption rates. By leveraging AWS as a robust data lake, and facilitating data transformation and visualization, credit unions can gain a deeper understanding of their members, drive revenue growth, and enhance data-driven decision-making.

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Architecture Diagram

[Architecture diagram description]

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Well-Architected Pillars

The AWS Well-Architected Framework helps you understand the pros and cons of the decisions you make when building systems in the cloud. The six pillars of the Framework allow you to learn architectural best practices for designing and operating reliable, secure, efficient, cost-effective, and sustainable systems. Using the AWS Well-Architected Tool, available at no charge in the AWS Management Console, you can review your workloads against these best practices by answering a set of questions for each pillar.

The architecture diagram above is an example of a Solution created with Well-Architected best practices in mind. To be fully Well-Architected, you should follow as many Well-Architected best practices as possible.

  • Amazon CloudWatch provides comprehensive visibility into system performance and health, enabling you to configure CloudWatch alarms that invoke automated actions for proactive issue resolution. CloudTrail maintains a detailed audit trail of API calls and configuration changes, enhancing compliance and security efforts. AWS Glue automates data management processes, offering automated schema discovery, classification, and catalog management, even for large datasets.

    Read the Operational Excellence whitepaper 
  • AWS DMS offers data protection during transit through its encryption capabilities, and Amazon S3 simplifies security by automatically encrypting all new objects at rest. IAM policies adhere to the principle of least privilege, scoping permissions to the minimum required. Additionally, Lake Formation defines granular security policies, restricting access at the database, table, column, row, and cell levels. AWS Key Management Service (AWS KMS) centrally manages encryption keys used across AWS services.

    Read the Security whitepaper 
  • Amazon S3 provides highly durable and redundant storage, replicating data across multiple Availability Zones. Amazon S3 versioning preserves, restores, and retrieves previous object versions. To further improve reliability, Amazon Redshift enhances data warehouse resilience through automatic backups, failure remediation, and multi-AZ deployment options. Amazon EMR provides configuration options to help you control automatic termination of clusters once steps are completed and to terminate clusters due to errors or issues before processing.

    Read the Reliability whitepaper 
  • Amazon EMR optimizes data processing by enabling right-sizing of clusters, dynamic scaling, and preconfigured environments. Amazon Redshift unlocks performance potential through features like partitioning, columnar compression, and query tuning so you can optimize data processing and reduce storage and I/O requirements. With Lake Formation, you can streamline data lake management by simplifying the process of identifying and moving data into a centralized repository, whether that data is structured or unstructured.

    Read the Performance Efficiency whitepaper 
  • Amazon S3 Intelligent-Tiering and lifecycle policies automate cost savings by seamlessly moving data to the most cost-effective storage tiers. Amazon EMR optimizes costs through auto-scaling and Amazon Elastic Compute Cloud (Amazon EC2) Spot instance utilization. Additionally, Amazon Redshift offers reserved sodes for steady-state workloads and Amazon Redshift Serverless for cost-effective scaling of unpredictable workloads.

    Read the Cost Optimization whitepaper 
  • The energy-efficient infrastructure of Amazon S3 and the resource optimization capabilities of managed services like Amazon Redshift, Amazon EMR, AWS DMS, QuickSight, and Lake Formation reduce environmental impact and lower overall IT footprint and carbon emissions compared to running on-premises with physical servers and hardware.

    Read the Sustainability whitepaper 
Case Study

Transforming the Member Experience Using Amazon Redshift with Together Credit Union

This case study demonstrates how Together Credit Union in financial services unlocked near real-time business intelligence using a data lake built on AWS.


The sample code; software libraries; command line tools; proofs of concept; templates; or other related technology (including any of the foregoing that are provided by our personnel) is provided to you as AWS Content under the AWS Customer Agreement, or the relevant written agreement between you and AWS (whichever applies). You should not use this AWS Content in your production accounts, or on production or other critical data. You are responsible for testing, securing, and optimizing the AWS Content, such as sample code, as appropriate for production grade use based on your specific quality control practices and standards. Deploying AWS Content may incur AWS charges for creating or using AWS chargeable resources, such as running Amazon EC2 instances or using Amazon S3 storage.

References to third-party services or organizations in this Guidance do not imply an endorsement, sponsorship, or affiliation between Amazon or AWS and the third party. Guidance from AWS is a technical starting point, and you can customize your integration with third-party services when you deploy the architecture.

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