Catch Bad Data Before
It Pollutes Your System
Prevent invalid records from entering your database with strict, row-level validation rules. Isolate errors without stopping the entire job, ensuring good data always gets through.
Data Integrity
Stop Cleaning Data After It's Imported
Manual spot-checks fail. Relying on downstream systems to catch errors creates pollution. Move your data quality gates upstream into a dedicated validation environment.
Stop Data Pollution
Block invalid records (e.g., duplicate emails, negative prices) before they ever reach your production system.
Intelligent Feedback
Replace cryptic system errors with clear, actionable messages that explain exactly why a specific row failed.
Non-Destructive Error Catching
Validation failures are flagged for review without discarding the surrounding valid data, ensuring you capture the full context of every error.
Workflow
From Source to Clean Import
A rigorous validation pipeline that separates valid data from exceptions.
Define Validation Logic
Leverage the full power of the Logic Builder—variables, If/Then blocks, and lookup tables—to create complex, cross-field validation rules.
Real-Time Validation Checks
The engine validates every row against your rules. Invalid records are flagged in the report with specific error messages, enabling targeted remediation.
Review in Data Viewer
Use the tabular Data Viewer to inspect results. Filter by 'Show Errors Only' to focus your attention on records that need fixing.
Resolve & Export
Export a report with error cells highlighted. Send this back to the client for correction or fix it internally before final import.
Why teams choose this approach
Unlike manual spot-checks or reactive error fixing, our validation engine catches bad data *before* it enters your system — preventing pollution and downstream cleanup.
Control & Safety
Enforcement You Can Trust
Enterprise-grade safeguards designed for high-stakes data migration projects.
Proactive Type Safety
The system automatically scans for and handles mixed data types to prevent schema corruption.
Validation Imports
Don't rebuild rules. Import validation logic from existing templates to ensure consistency across projects.
Sandboxed Execution
All custom validation logic runs in a secure, isolated Python environment.
Audit Trail
Every validation failure is logged, categorized, and available for post-mortem analysis.
Use Cases
The go-to for data import solutions
For repeatable CSV, Excel, and JSON imports — not streaming ETL or analytics workflows.
Client Data Onboarding
Standardize messy client data instantly with AI-powered mapping and reusable templates
Software Implementation
Accelerate go-live times by empowering non-technical teams to handle data migrations
Legacy System Migrations
De-risk high-stakes migrations with visual validation and automated data transformation
Software Vendors
Win more deals and boost customer satisfaction by simplifying onboarding
Consultancies
Scale your service delivery by building a library of reusable mapping templates
Operations
Streamline product catalog mapping and inventory data synchronization
Full Access for 30 Days
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1-on-1 Onboarding & Support
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Product Roadmap & Features
Get first say in the future of DataFlowMapper. Your feedback shapes our platform.
The visual data transformation platform that lets implementation teams deliver faster, without writing code.
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