This guide walks you through exporting data quality results for your Attribute Value Mappings. The export helps you analyze Data Quality failures and identify areas to improve mapping integrity.
Article Contents:
Step-by-Step Export Process
Follow the steps below to export your Data Quality.
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- Click Export Data Quality
- Find the Export Data Quality button located within the Mapping Tab.
- Choose Delivery Method
- Direct Download: The file will be downloaded immediately once generated.
- Email: The export will be sent to your registered email address.
- Select Recipient Requirement Set(s)
- Choose one or more requirement sets from the list. This is a required field.
- Optional: Include Unmapped Attributes
- Select Yes if you want to include attributes that are not mapped; otherwise select No.
- Optional: Include Disabled Mappings
- Select Yes to include mappings that are currently disabled (archived/deleted mappings are excluded). Select No to omit them.
- Add Products
- Click Add products and select the products you want to include. Data quality will run only on recipients linked to those products. This is a required step.
- Tip: The product selection uses the existing Product Information Panel (PIP) filter functionality, so you can search and filter as needed.
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- Confirm and Export
- Review your selections and click the Export button. Your choices are saved per user per session, so the next time you export, your previous selections will be remembered.
- You'll receive a notification in the Notification Center when the file is ready. If you chose email, it will be sent to you.
Understanding the Exported File
The exported file is an Excel workbook containing two tabs: Summary and Data 1.
Tab 1: Summary
The Summary tab helps you see the big picture before diving into row-level details.
Top Left Section:
- Recipient Name: The recipient associated with the data.
- Total Error Types: Count of distinct error types for that recipient. Look for recipients with high counts—these may need attention first.
- Distribution of Total Error Types: Breakdown of errors by type. This shows whether errors are spread across many categories or concentrated in one.
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Circle Graph:
A quick visual cue showing error distribution. Large slices indicate the most common issues—use this to spot patterns at a glance.
Attribute Error Count Table:
- Attribute Id - Syndigo Unique identifier for the target attribute
- Attribute Name – Name of Target Attribute
- Error Count – Total number of errors affecting the attribute
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Enabled Mappings affected by Data Quality Errors Chart:
This chart uses horizontal lines from each Target Attribute GUID on the left to a 0-12 scale on the right. The line endpoint indicates the number of Data Quality errors for that mapping.
Tab 2: Data 1
This tab contains detailed row-level data with the following columns:
| Column Title | What It Tells You |
| Source Attribute Guid | Syndigo Unique identifier for the source attribute |
| Source Attribute Name | The field name from your original data |
| Source Attribute Value | The actual value from your data that was mapped |
| Target Attribute Guid | Syndigo Unique identifier for the target attribute |
| Target Attribute Name | The standard field the system expected |
| Target Attribute Value | The Mapped/Transformed Value |
| Target Parent Attribute Name | Parent field context for the target attribute |
| Map Status | Whether the mapping was active, disabled, or unmapped at time of export |
| Data Layer | The data layer associated with the mapping |
| Recipient Name | Which recipient the data belongs to—helps isolate issues to specific recipients |
| Locale | Language or regional context for the data |
| Requirement Set Name | The rule set applied to validate the data |
| Requirement Set Version | Version of the requirement set used |
| Category | Product category associated with the mapping |
| Product Name | The product linked to the recipient; useful for cross-product comparisons |
| Company Defined Unique Id | Your organization's internal identifier for the recipient or product |
| Error Message | Why the validation failed. Common errors include: "Value not found in dataset," "Invalid format," "Missing required mapping" |
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Large Data Sets:
If your export exceeds Excel's row limit, the system will automatically split the data into multiple files, each with up to 1 million rows. You'll receive all files in your download or email.
Next Steps After Export
- Identify patterns – Use the Summary tab error list to spot the most frequent issues. Large slices in the circle graph or high totals in the error message section are good places to start.
- Drill down in the Data tab – Filter on a specific error message or product to see exactly which source values are causing failures.
- Cross-check with mappings – Open your Mappings tab and review mappings for the attributes, products, or recipients with high error counts.
- Fix in batches – If the same error appears for many recipients, update the mapping once rather than fixing rows individually. For example, if a source value "N/A" should map to "Not Applicable," update the mapping rule rather than editing each row.
- Re-run data quality – After making changes, run another export to verify improvements. Your previous selections will be remembered (stickiness), so you can quickly repeat the export.
Want to Learn More?
Click the links below to learn more about Mapping and Transformation functionality.
Revision #:
3 of 3
Last update:
06-16-2026
05:21 PM
Updated by:
