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Yggdrasil requires explicit approval of column mappings before running scans. This ensures transparent, auditable data transformations.

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Why Explicit Approval?

This is a core design decision:
Transparent mapping principle: No data transformations happen behind the scenes. You must explicitly confirm which CSV columns map to which compliance schema fields.
Benefits:
  • Auditability: Every scan has a documented mapping configuration
  • Error prevention: Catch incorrect mappings before generating false violations
  • Control: Override AI suggestions when you know your data better

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Standard Schema Fields

Yggdrasil maps your CSV columns to these standard fields:
FieldDescriptionExample CSV Columns
amountMonetary valueAmount, Transaction_Amount, Payment_Value
stepTime referenceTimestamp, Date, Step, Period
accountPrimary entityAccount_ID, Sender, User_ID, Employee_ID
recipientSecondary entityRecipient, Destination, To_Account
typeCategory/classificationTransaction_Type, Event_Type, Category
Not all fields are required. Only map fields that exist in your dataset and are relevant to your compliance rules.

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Mapping Review Process

1

Review AI suggestions

After upload, Yggdrasil shows suggested mappings with confidence scores:
{
  "amount": "Transaction_Amount",  // 98% confidence
  "account": "Sender_ID",          // 95% confidence
  "type": "TX_Type"                // 87% confidence
}
High confidence (>90%) usually means the AI detected a known dataset format.
2

Adjust mappings if needed

Click any field to change its CSV column mapping:
  • Select a different column from the dropdown
  • Leave unmapped if not applicable
  • The system shows a preview of sample values for verification
3

Set temporal scale

If your rules use time windows, specify how to interpret your time column:
  • 1.0 = 1 step = 1 day (default for GENERIC datasets)
  • 24.0 = 1 step = 1 hour (default for IBM AML / PaySim)
Example: If your CSV has step values 1, 2, 3 and scale is 24.0, the engine treats step 1→2 as a 24-hour window.
4

Confirm mapping

Click “Confirm Mapping” to save your configuration. This generates a mapping_id and marks the audit ready to scan.

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Mapping Storage

Confirmed mappings are stored in-memory with the scan configuration: 
{
  "mapping_id": "a1b2c3d4-...",
  "upload_id": "e5f6g7h8-...",
  "mapping_config": {
    "amount": "Transaction_Amount",
    "account": "Sender_ID",
    "type": "TX_Type"
  },
  "temporal_scale": 24.0
}
This mapping is applied during the scan and saved with the scan results for auditability.

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What Happens During Confirmation

When you click “Confirm Mapping”:
  1. Validation: System checks that at least one field is mapped
  2. Storage: Mapping config is saved with a unique mapping_id
  3. Readiness check: Scan button becomes enabled
  4. Response: API returns { mapping_id, ready_to_scan: true }
The mapping is stored in-memory, not persisted to the database. If you refresh the page, you’ll need to re-upload and re-confirm.

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Advanced: Cross-Field Comparisons

Some compliance rules compare two fields (e.g., “sender balance != recipient balance”). For these rules, both fields must be mapped: 
{
  "conditions": {
    "field": "sender_balance",
    "operator": "not_equals",
    "value": "receiver_balance",
    "value_type": "field"  // Indicates value is another column
  }
}
If your CSV doesn’t have the required columns, you can:
  • Disable the rule (toggle it off in the Rules screen)
  • Add the missing columns to your CSV and re-upload

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Common Mapping Scenarios

You’re auditing consent records. Your CSV has:
  • data_subject_id → map to account
  • consent_date → map to step
  • No monetary values → leave amount unmapped

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Scenario 2: AML Transaction Monitoring

You’re scanning financial transactions. Your CSV has:
  • transaction_amount → map to amount
  • timestamp → map to step
  • sender_account → map to account
  • receiver_account → map to recipient
  • transaction_type → map to type

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Scenario 3: SOC2 Access Logs

You’re auditing system access. Your CSV has:
  • user_id → map to account
  • login_time → map to step
  • action → map to type
  • No amounts or recipients → leave unmapped

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Type Coercion

CSV files produce string values. The engine automatically coerces types:
  • "true" / "false" → boolean
  • "16" / "99.5" → numeric
  • Date strings → parsed as timestamps (if used in temporal rules)
You don’t need to pre-format your CSV — Yggdrasil handles type conversion during scan execution.

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Next Steps

After confirming your mapping:
  1. Optionally run PII detection → PII Detection
  2. Review rules and toggle any you want to disable
  3. Run the compliance scan → Compliance Scanning

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