Modernizing Business Intelligence (BI) without proper data testing is like building a high-speed train on shaky tracks. BI systems need to pull data from various sources (legacy systems, cloud platforms, APIs), transform it, and deliver insights through reports and dashboards. Testing this entire flow is data-intensive, and manual TDM slows down delivery, increases errors, and poses security risks when handling sensitive financial/PII data. Application testing must validate the efficacy of integrations between large-scale data warehouses (such as Snowflake, Oracle DW, Google BigQuery, Amazon Redshift) with modern BI and reporting tools (such as Tableau, Power BI, SAP Webi, Looker).

Because public trust, compliance, and accuracy are critical, rigorous and repeatable testing becomes that much more essential to ensure highly secure modernization. This is where we make a difference for our customers by using our Automated Test Data Management (TDM) tool (IntelliSWAUT) and framework.

Our tools and framework are used by some of the top federal lending institutions to modernize and de-risks Business Intelligence (BI) and Reporting. Use of open source tools like Playright along with our No-Code/Low-Code testing tool (IntelliSWAUT) is helping our customers to accelerate the process of test data provisioning, masking, and validation of test data while significantly reducing testing costs.

Some benefits experienced by testing teams with the help of Sun Technologies’ deployment of Automated Test Data Management and Opensource Tools:

1. Rapid, On-Demand Test Data Provisioning

• Auto-generates production-like data subsets for each test environment instantly
• Reduces setup time for QA, dev, and UAT teams from days to minutes
• Supports parallel test cycles across BI dashboards, ETL pipelines, and reports

Example: Quickly provisioning clean, sample data from loan origination, underwriting, and servicing systems for Tableau dashboard testing in SBA or HUD.

2. Data Masking to Protect PII & Ensure Compliance

• Automatically masks sensitive data like SSNs, tax IDs, and financials before use in non-prod environments
• Ensures FedRAMP, NIST, and agency-specific compliance
• Allows more stakeholders (e.g., contractors, offshore teams) to access test environments safely

Example: Masking borrower identities in USDA Rural Development loan reports before running tests in Power BI environments.

3. Versioned, Reusable Test Data Sets

• Stores reusable data snapshots that can be applied to different scenarios (e.g., default scenarios, high-volume disbursements)
• Helps test historical trends and edge cases reliably
• Supports regression testing for BI changes with consistent datasets

Example: Replaying previous quarter’s loan performance data to test a new Tableau dashboard in Fannie Mae.

4. Integrated Test Automation for CI/CD

• Integrates with automated testing tools (e.g., Selenium, Postman, Playwright, PyTest, DataOps tools)
• Auto-refreshes test data as part of the CI/CD pipeline
• Reduces manual errors, supports faster sprints, and aligns with agile delivery

Example: As soon as new ETL logic is deployed in Snowflake, a TDM tool triggers synthetic test data creation, enabling automated report validation in minutes.

5. Synthetic Data Generation for Edge Case Testing

• Automatically creates synthetic data for rare but important BI scenarios (e.g., delinquent borrowers, high-risk fraud flags)
• Enables testing of “what-if” BI models (e.g., default spike in a specific region)

Example: Generate test cases for unusually large PPP loan amounts or unusual repayment behavior for HUD’s risk dashboards.

6. Environment Synchronization

• Syncs data across multiple test environments (UAT, QA, staging) so BI dashboards reflect consistent inputs
• Avoids mismatch errors during multi-team testing cycles

Example: Ensuring that a disbursement recorded in a loan servicing system appears identically in the data warehouse and the Power BI compliance report.

7. Data Subsetting for Cost Optimization

• Generates smaller, targeted test datasets that still maintain data integrity
• Reduces cloud storage and processing costs for test environments

Example: Only provisioning loans originated in the last 90 days for BI report testing instead of full historical loads.

Some Key Objectives of BI Modernization Achieved by Our Clients:

• Faster decisions for loan approvals, servicing, and policy-making
• Stronger fraud detection and risk management through predictive analytics
• Real-time transparency for citizens, agencies, and Congress
• Better service delivery to borrowers across communities

Below are a few outcomes of automating Test Data Management that has resulted in modern reporting and analytics for our clients.

1. Modernizing Reporting and Analytics Involving PPP Loan Fraud Detection

Challenge: When implementing the Paycheck Protection Program (PPP), banks face the challenge of managing billions in emergency loans while identifying fraud.

Modernization Move:

• Integrate legacy and mainframe systems with analytics vendors to create real-time fraud detection dashboards
• Use cloud-based BI tools like Power BI and Tableau to visualize loan disbursement and suspicious patterns
• Integrate IRS, Treasury, and bank data to enhance oversight

Impact:

• Helped auditors flag suspicious applications instantly
• Saved millions in fraudulent payouts
• Increased transparency for congressional oversight

2. Modernizing Risk Management Processes for Housing and Urban Development

Challenge: A housing loans process needed better monitoring and performance tracking.

Modernization Move:

• Replace Excel-upload based reports and an outdated dashboard with an interactive BI dashboarding system
• Use data warehouse integration to consolidate credit, appraisal, and underwriting data
• Apply machine learning models to predict loan default risks

Impact:

• Improved the loan underwriting team’s ability to proactively manage risks
• Enhanced collaboration between field offices and central operations
• Reduced manual reporting errors and increased decision-making speed

3. Implementing Self-Service Analytics for Lenders

Challenge: Lenders needed easier access to insights about loan status, credit risk, and market trends.

Modernization Move:

• Launch Fannie Mae Data Dynamics, a modern BI portal with interactive visualizations and trend analysis
• Enabled self-service analytics for lenders, allowing them to compare performance and make data-driven decisions
• Integrated with Fannie’s cloud-based systems and dashboards

Impact:

• Reduced call volume to Fannie support teams
• Gave lenders real-time access to insights without IT bottlenecks
• Supported better loan pricing and underwriting decisions

4. Modernizing Loan Servicing Automation

Challenge: A loan provider wanted to streamline how loans were tracked and serviced across geographies.

Modernization Move:

• Migrate to a cloud BI environment using AWS and Power BI
• Centralize loan data from multiple state offices and divisions
• Develop predictive models to identify borrowers at risk of default

Impact:

• Improved response time to distressed borrowers
• Enabled field officers to make quicker, localized decisions
• Enhanced loan servicing efficiency with fewer manual errors

5. Modernizing Portfolio Performance Monitoring

Challenge: Better visibility into loan guarantees and international credit exposure.

Modernization Move:

• Adopt a modern data warehouse and real-time BI dashboards
• Integrate external economic indicators and borrower data
• Built automated alert systems for geopolitical risk and payment delays

Impact:

• Enabled proactive risk mitigation strategies
• Enhanced portfolio transparency for leadership and oversight boards
• Reduced manual reporting time by over 40%

Overall Objectives Achieved by Our Customer Using Sun Technologies for BI Modernization

• Faster decisions for loan approvals, servicing, and policy-making
• Stronger fraud detection and risk management through predictive analytics
• Real-time transparency for citizens, agencies, and Congress
• Better service delivery to borrowers across communities

There are some very important considerations that the testing team needs to be aware of when modernizing Business Intelligence (BI) for the enterprise. Connect with Sun Technologies testing experts if you are building or modernizing BI. Reach out for outlining a roadmap and get tooling stack recommendations to meet key business objectives while meeting all aspects critical for compliance.