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Reporting — Row Count Compare Report
Compare source and target record counts across reconciliation scenarios to quickly detect data volume discrepancies.
Overview
The Row Count Compare Report compares record counts between source and target data sets across reconciliation scenarios. It provides a count-level view of data volume discrepancies, enabling teams to detect missing or extra records without running a full field-level comparison.
Prerequisites
- You are logged in to Data Trust with a Pro-User or Admin Pro-User role.
- At least one reconciliation scenario with row count comparison has been executed.
Accessing the Report
Path: Data Trust › Reporting › Row Count Compare ReportFrom the Reporting module, click the Data Quality Metrics Dashboard link in the navigation to see the full list of available dashboards including Row Count Compare. All Reporting dashboards are accessible from this navigation panel, so you can switch between them without navigating back to the main Reporting home.
Click 'Row Count Compare Dashboard' in the dashboard list to open the report and load all available reconciliation scenario comparisons. The dashboard automatically fetches the most recent execution data for all scenarios that have row count comparison configured.
The Scenarios view lists all reconciliation scenarios with their source row count, target row count, discrepancy value, and overall match status displayed per row. Rows where the source and target counts differ are highlighted so you can immediately identify which scenarios have record volume discrepancies.
Applying Filters
Click the Filter icon in the report toolbar to open the filter options panel where you can narrow the report to specific Jobs, Profiles, or individual Scenarios. Applying filters before reviewing results is useful when you are investigating row count issues for a specific data pipeline or set of reconciliation scenarios.
The Select Jobs pop-up allows you to choose one or more Jobs whose scenarios should be included in the Row Count Compare Report, scoping the analysis to a specific workload. Selecting a job-level filter is helpful when your organization runs separate reconciliation jobs for different business units or data domains.
After selecting filter criteria, click Preview to see the list of scenarios and their row counts that match your selections before applying the filter to the full report. This preview step prevents you from accidentally applying a filter that excludes all data or selects the wrong set of scenarios.
Understanding Report Components
The Row Count Compare Dashboard is divided into a Summary Component at the top and a Detailed Grid below, each providing a different level of aggregation and analysis. The Summary Component gives a platform-wide view of total record volumes, while the Detailed Grid lets you examine discrepancies at the individual scenario level.
The Summary Component shows aggregated row count totals — including total source records, total target records, total matched counts, and the overall discrepancy percentage. A high overall discrepancy percentage in the Summary Component is a signal that multiple scenarios have record volume issues that need to be investigated.
The Detailed View expands each scenario's row count comparison to show the individual source table counts, target table counts, and the exact record-level discrepancy amount. Use this view to identify whether a discrepancy is coming from one large table or spread across multiple smaller tables within the same reconciliation scenario.
Sorting Results
Click the dropdown icon next to any column header to access sort and filter options for that column, allowing you to order rows by source count, target count, or discrepancy. Sorting by Discrepancy in descending order is the quickest way to surface the scenarios with the largest record volume gaps at the top of the list.
Viewing Result History
The Result History column shows a mini trend indicator for each scenario, representing the pass/fail status of its row count comparison across multiple recent executions. A trend that shifts from passing to failing indicates that a record volume discrepancy has recently appeared and should be investigated as a potential data pipeline issue.
Clicking the Result History indicator opens the full details panel, listing every past execution with the exact source count, target count, and discrepancy for each run. This historical view is useful for determining whether a record count discrepancy is a new issue or has been present — and possibly growing — over multiple execution cycles.
Hovering over any dot in the Result History trend chart reveals a tooltip showing the exact execution date, source count, target count, and discrepancy value for that run. The tooltip makes it easy to pinpoint the specific date when a record count discrepancy first appeared, which can help correlate the issue with upstream data events.