Troubleshooting checklist: Contextual Data Mashup upload issues

1. File format & structure

• CSV Format: Ensure the file is in CSV format. Other formats (Excel, TXT, etc.) are not supported.

• Encoding: Use UTF-8 encoding. Avoid special characters or BOM headers that may cause parsing issues.

• Column Names: Remove spaces from column names and ensure they match the expected schema exactly.

• Header Row: The first row must be the header, with correct attribute names.

2. Data types & values

• Boolean Fields: Use True and False (case-sensitive) for Boolean columns.

• Date Fields: Use the format yyyy-mm-dd (e.g., 2025-07-15). Other formats like MM/DD/YYYY will cause errors.

• Reference Columns: For TechSpend mashups, only Vendor Name or Spend Category can be used as reference columns, not both.

• Key Fields: Ensure all records have values for attributes marked as Key.

3. Schema & attribute matching

• Schema Consistency: The uploaded dataset’s schema (column names and data types) must match the existing dataset if updating.

• Attribute Types: If attribute names match but data types differ, the system will warn you. Resolve any mismatches before uploading.

4. Permissions & access

• User Roles: Only users with Manage Contextual Data or Manage Organization roles can upload mashups.

• Feature Flags: Ensure your organization is enabled for the feature if using a new UI.

5. Upload process

• UI Status: If the upload status remains "unknown" for a long time, check for backend processing issues or entitlement problems.

• Preview Window: If the "Continue" button is grayed out, check for file format, column name, or data type issues.

• Error Logs: Review error files generated during upload for specific parsing or validation errors (e.g., date parsing errors)

6. Common error scenarios

• Date Parsing Errors: If you see errors like error while parsing ... to Date, double-check the date format in your CSV.

• Reference ID Issues: If data does not correlate to normalized data, ensure correct reference IDs are used.

• Target Model Invalid: This may indicate schema or reference mismatches.

7. Documentation & support

• Official Documentation: Refer to Managing Contextual Data Mashup for the latest requirements

• Contact Support: If all else fails, attach your test and error files when raising a support ticket for faster resolution.

TIP: Always validate your CSV with a small test upload before attempting a full dataset.

• Successfully upload contextual data mashups without encountering format, schema, or permission-related errors.
• Identify and resolve common issues such as date parsing failures, reference mismatches, and UI upload blocks.
• Ensure alignment between uploaded data and existing datasets to prevent schema conflicts.