Representative engagementData Quality
Source-to-Target Data Validation
- Challenge
- An organization moving reporting to a new data warehouse relied on spot checks of a few records to confirm each load. Differences between source systems and reports were discovered by business users, weeks after the fact.
- Approach
- Mapping documents were translated into executable SQL validations covering counts, completeness, transformation rules and totals at each layer. Checks were scheduled to run after every load, with results summarized for the data team.
- Technologies
- SQL
- SQL Server
- Databricks
- Python
- Azure DevOps
- Business outcome
- Differences are identified at the layer where they occur, before they reach reports, and migration sign-off is based on full reconciliation rather than samples.
Representative engagementTest Automation
Regression Automation Transformation
- Challenge
- A product team spent several days manually re-checking core workflows before every release. An earlier automation attempt had become flaky and was no longer trusted.
- Approach
- Automation candidates were prioritized by risk and frequency. Business rules moved to API-level tests, and a small, stable set of browser tests covered critical journeys. The suite was integrated into the CI pipeline with clear reporting.
- Technologies
- Playwright
- TypeScript
- REST APIs
- Postman
- GitHub
- CI/CD
- Business outcome
- Core regression runs automatically on each change, testers focus on exploratory work, and the team can release on its own schedule rather than waiting for a test window.
Representative engagementSoftware Quality
Application Release Quality Improvement
- Challenge
- A customer-facing application saw recurring defects after releases. Testing happened late, requirements were loosely defined, and go/no-go decisions depended on individual judgment.
- Approach
- A QA strategy introduced acceptance criteria reviews, risk-based test planning, integration and end-to-end coverage, and a written release checklist with a quality summary for stakeholders.
- Technologies
- Azure DevOps
- Selenium
- Postman
- SQL
- JMeter
- Business outcome
- Defects are found earlier in the cycle, stakeholders see the same quality picture before each release, and release decisions are made on evidence.