List Processing With Speed and Precision

The import module handles partner data in CSV, Excel and XML formats coming from your various sources. During import, it runs validations to catch formatting issues and missing fields right away.

You can set up automated schedules or manually trigger imports as needed, with detailed logs tracking success rates and issues for each run.

The system maintains links between related records while processing both one-time partner lists and recurring transaction data. When needed, you can add pre-processing filters and transformations to prepare data before the main import phase.

Analysis tools measure quality levels across your imported datasets and identify incomplete records.

The system generates statistical breakdowns that reveal value clusters and outliers, while letting you apply custom quality rules to match your specific standards.

By calculating scores for both individual fields and complete records, you can quickly spot problem areas. These tools also track quality patterns across different data sources and time periods, documenting all findings in detailed reports for further investigation.

Standardization tools work with your formatting rules to normalize company names, addresses and identification numbers across all records.

You can build specific rule sets for different types of partner data, creating documented workflows that handle multiple standardization steps.

While standardizing records for system use, the engine preserves original values and logs all changes for reference. When records don't meet standardization rules, they move to review queues where you can refine the rules based on new data patterns.

The matching system examines company names, addresses and other identifying fields to locate duplicate records in your data.

You control the matching rules and thresholds based on your data quality requirements, while the system processes records in optimized batches.

Before any merging occurs, you can review match scores and make informed decisions about each case. The system always keeps detailed logs of matching decisions and manual overrides, while flagging uncertain matches for additional research.

The version control system documents changes throughout your partner data processing.

You can examine different versions to understand what changed between runs, with the ability to restore previous versions while preserving relationship data.

The audit trail shows the full history of who made changes and when, giving you insights to analyze processing patterns and improve workflows.

By maintaining links to source records, the system creates a complete historical record of your data processing.