Data Migration Testing Infographic

Data Migration Testing

Migrate data with confidence, not guesswork, with QuerySurge's no-code solutions.

The Manual Trap

Legacy migration testing relies on "sampling"—checking random rows of data manually. This approach is statistically flawed. When you only test a fraction of your data, bad data hides in the unverified majority, leading to production failures and compliance risks.

⚠ Manual testing typically validates less than 1% of total data volume.

The Automation Architecture

Modern solutions like QuerySurge bypass the user interface to validate data at the database level. By automating the comparison between Source and Target systems during the ETL (Extract, Transform, Load) process, organizations can ensure absolute data parity.

🗄️

Legacy Source

❯

⚙️

ETL Process

❯

☁️

Target System

QuerySurge Automation

✓ Pulls from Source
✓ Pulls from Target
✓ Compares 100% of Records

Accelerating Delivery

Manual testing is a bottleneck. Human testers can only validate a few hundred records per hour visually. Automated engines utilize Big Data processing power to compare millions of records in minutes. This speed enables Continuous Integration/Continuous Delivery (CI/CD) pipelines to function without stalling for data testing.

Low

Manual ROI

1000x

Faster

Strategic Impact

Moving to an automated strategy isn't just about speed; it's about mitigating business risk. Automation provides a full audit trail for compliance, ensures zero data loss, and drastically reduces the cost of fixing defects by finding them early.

1 Full Audit Trail

2 Regulatory Compliance

3 Early Defect Detection

Universal Connectivity

QuerySurge connects to virtually any data store.

Data rarely stays in one format. Modern migrations involve moving from on-premise legacy mainframes to cloud data warehouses, or from flat files to NoSQL lakes. An effective testing tool must be technology-agnostic.

Oracle & SQL Server

Hadoop & Big Data

Amazon Redshift

Snowflake & Azure

XML & JSON

Flat Files