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Documentation Index

Fetch the complete documentation index at: https://docs.yrka.io/llms.txt

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The Import Center in Yrka is the review-first intake surface for payroll history, schedule events, resource files, and employee records. Every import follows the same pattern: upload a supported file, map columns to Yrka fields, review validation results, and commit only the rows you have reviewed and approved. Nothing is applied to production records without your explicit commit — imports do not silently mutate data.
XLS/XLSX workbook imports are currently disabled. Convert workbook files to CSV or TSV before uploading. This applies to payroll, schedule, and other import types.

Import Center overview

Open Admin Tools > Imports to access the Import Center. The main view shows domain import mode tabs and a data-movement queue that surfaces integration sync events, provider handoffs, notification delivery evidence, and failed records alongside your file imports.

Import modes

ModeWhat you import
PayrollHistorical payroll records, timecard history, pay data
ScheduleSchedule events and shift assignments
ResourcesSource documents for Resources review and knowledge chat
EmployeesEmployee roster data (available when enabled for your organization)
All historyCombined view of all import activity, provider sync jobs, webhook replay candidates, and handoffs
FailedBatches and rows that could not commit and need attention
Needs reviewBatches waiting on mapping, validation decisions, or admin action

Payroll imports

Payroll imports let you bring historical timecard and pay data into Yrka. After import, committed records appear in Timekeeping and Payroll contexts.

Supported file profiles

  • Generic CSV/TSV — standard comma- or tab-separated payroll export
  • Foundation Payroll — Foundation-oriented column layout
  • QuickBooks Time — QuickBooks Time export format
  • Custom — configured column mappings saved as a reusable profile

Importing payroll data

1

Open Payroll in Imports

Go to Admin Tools > Imports and select Payroll. You need the payroll.import permission to upload or commit.
2

Upload the file

Select your CSV or TSV file. Yrka creates an import batch, stores normalized row previews, and auto-detects common column names.
3

Review detected columns and employee matching

The preview shows detected columns alongside Yrka fields, matched employees (matched by employee number, payroll ID, email, or name), duplicate timecard row flags, and any validation warnings. Check each before mapping.
4

Map source columns

Map each source column to the corresponding Yrka field. For common profiles (Foundation, QuickBooks Time), many columns will auto-map. Review auto-mapped columns before committing — do not assume auto-mapping is always correct.
5

Revalidate

After updating mappings, revalidate the batch. Resolve any remaining errors or warnings before proceeding.
6

Commit ready rows

Select Commit to apply ready rows only. Committing a payroll batch can:
  • Update employee payroll fields
  • Create missing job catalog rows
  • Insert historical timecards
  • Adjust PTO/VAC balances through the leave ledger
7

Review the import work item

Committing creates an import_review admin Inbox work item. Review and resolve it to complete the import audit trail.
Commit applies ready rows only. Rows with unresolved errors or validation failures are skipped. Review the skipped/error row export to identify records that need correction outside Yrka.

Schedule imports

Schedule imports bring shift and assignment data from external systems into your Yrka schedule calendar.

Supported file formats

  • ICS — standard calendar export format (from Google Calendar, Microsoft 365, Apple Calendar, or other calendar tools)
  • CSV — schedule data in comma-separated format with common schedule column patterns

Importing schedule data

1

Open Schedule in Imports

Go to Admin Tools > Imports and select Schedule. You need the schedule.import permission. You can also access schedule import from the Schedule header’s Import shortcut.
2

Upload the file

Upload your ICS or CSV file. Yrka creates a schedule import batch, stores row previews, detects common schedule columns, and matches employees by name, email, or employee number.
3

Review row previews and employee matching

Check each row for matched employees, flagged duplicates, and conflicts with existing schedule events. Rows without matched employees cannot be committed until the identifier is corrected.
4

Select the target calendar

Before committing, confirm the target Schedule calendar shown on the batch. This is the internal Yrka calendar where committed events will land. Provider calendar names and Yrka schedule calendars are separate — make sure the right one is selected.
5

Commit ready rows

Commit reviewed rows. Each committed row inserts a schedule event and, where employees are matched, creates the corresponding assignment.
6

Review the schedule import work item

Committing creates a schedule_import_review admin Inbox work item. Resolve it after confirming the events look correct in Schedule.
If you use a calendar provider (Google Calendar, Microsoft 365, Apple Calendar ICS) through Integrations, those syncs also stage into the same Schedule import review workflow. Open Imports > Schedule to find and review provider-staged batches alongside manually uploaded files.

Review-first: the import safety model

Every import in Yrka is review-first. This means:
  • Uploads create a batch in review state — no data is applied yet
  • All imports generate an admin Inbox work item so the review is tracked
  • You commit only after inspecting row previews, employee matching, and validation
  • Committing applies ready rows only — rows with errors are skipped, not silently applied
This design prevents unreviewed data from entering production records. If an import file has problems, they surface in validation before you commit, not after.

Import history and failed views

Use All history to see every import batch, provider sync job, webhook replay candidate, staged source record, payroll handoff, and notification delivery attempt for your organization. Use Failed to focus on batches and rows that could not commit.
1

Find a failed batch

Open Failed or All history and sort or page the table to find the batch. The status column shows whether the batch failed, needs review, was archived, or succeeded.
2

Review the failure reason

Open the batch to see the safe error summary. Common causes include unmatched employee identifiers, unsupported columns, and validation conflicts with existing records.
3

Export skipped or error rows

Export error rows for correction outside Yrka, then re-upload a corrected file. Do not retry a failed batch with the same file if the source data needs correction.
4

Archive stale batches

Archive batches that should leave the active review queue once they are no longer needed. Archived batches remain available as audit evidence.

Troubleshooting

Check the employee identifier columns in your file — employee number, payroll ID, email, and name are the supported matching fields. Correct the identifiers in the source file and re-upload. Do not commit rows with unmatched employees if those employees must receive the imported records.
Compare the flagged rows with existing timecards or schedule events in Yrka. If the source data genuinely duplicates what is already in Yrka, skip or do not commit those rows. If they are different records that should both exist, investigate whether the duplicate flag is from a matching identifier conflict.
Convert the file to a supported CSV, TSV, or ICS format. XLS/XLSX workbook imports are currently disabled — do not attempt to upload workbook files.
Check Resend invite readiness in Integrations. Use the manual invite link fallback from Personnel for affected employees until domain and DNS verification are complete.
Resources import is the source review lane, not a file-row mapping lane. To approve and stage source documents for knowledge chat, work through the source review flow in Resources.
Check All history — the batch may have succeeded earlier or may not have started. The Failed view shows only batches and rows that reached a failed or error state, not pending or in-progress batches.