Data Testing
ETL, migration, and report testing with real reconciliation
Data defects are silent. A migration that loads without error can still drop rows, truncate values, or shift precision — and it usually surfaces at period close.
Source-to-TargetReconciliationSQLData QualityBI Reports
Technology Depth
Data testing coverage
Comprehensive ecosystem coverage backed by vetted senior principals and certified specialists.
Validation Types
Source-to-Target MappingRow Count ReconciliationData CompletenessData Transformation RulesReferential IntegrityDuplicate DetectionNull & Default HandlingPrecision & TruncationSlowly Changing DimensionsIncremental Load Testing
Platforms
SQL (Oracle / SQL Server / Postgres)SnowflakeDatabricksInformaticaTalendSSISdbtApache AirflowSpark
Reporting Layer
Power BITableauOracle AnalyticsOTBI & BI PublisherReport Figure ValidationDrill-down ConsistencyAggregation Accuracy
Migration Scenarios
Legacy to ERP MigrationCore Banking MigrationWarehouse RebuildCloud Data MigrationParallel Run ComparisonCutover ValidationHistorical Data Load
Enterprise Delivery
What data testing engagements deliver
- Reconciliation — counts, sums, and checksums between source and target
- Rule validation — every transformation rule tested independently
- Automated checks — repeatable SQL suites run on each load
- Report validation — figures traced from dashboard back to source
- Data quality profiling — identifying issues before they migrate
- Sign-off evidence — documented reconciliation for finance and audit
Sampling is not validation
Spot-checking a hundred rows out of a million proves very little. Reconciliation should be exhaustive and automated, because it will need to run again on every mock cycle.
- Full-population checks rather than sampled comparison
- Automated scripts reusable across every migration run
- Financial totals reconciled to the ledger, not just row counts
- Differences reported at record level for investigation
Common Questions
Frequently Asked Questions
Transparent insights into our delivery, pricing models, security compliance, and onboarding timelines.
Can you validate reports as well as the underlying data?
Yes. Report-level validation traces figures from the dashboard back through the warehouse to the source system, which is where most reporting disputes are actually resolved.