Oracle PeopleSoft and Google Sheets integration

What moves between them

The primary flow is from Oracle PeopleSoft into Google Sheets. Vendor master records, employee directories, purchase order summaries, and GL journal entries are read from PeopleSoft using HTTP Basic Auth or OAuth2 credentials, then written to matching Google Sheets tabs on a daily, weekly, or custom schedule. Each row carries the source record's natural key so updates can be matched and replaced rather than appended. The schedule typically runs outside business hours to avoid impacting the PeopleSoft instance. Because PeopleSoft provides no webhooks, ml-connector polls the configured REST endpoints and filters by date or modification timestamp to fetch only the records changed since the last run, reducing the load on both systems.

How ml-connector handles it

ml-connector stores both the PeopleSoft credentials (OPRID and password, or OAuth2 client ID and refresh token) and the Google Sheets service account key encrypted. For each scheduled run, it authenticates to Oracle PeopleSoft using the supplied credentials, polls the configured REST endpoints with date-range filters, and extracts the result sets as JSON. It then converts each record into a row using the customer-defined column mapping, authenticates to Google Sheets with the service account, and writes the rows to the target sheet using the batchUpdate API. Row matching is done by the natural key (vendor ID, invoice number, employee ID, etc.), so updates overwrite older rows rather than creating duplicates. If a REST call hits a timeout or PeopleSoft returns a 5xx error, ml-connector backs off and retries. Because Google Sheets API has rate limits and the service account quota is per project, ml-connector queues writes and batches them into single API calls. All successful and failed records are logged in the audit trail with the source JSON, target row, and any error messages, so failed rows can be reviewed and replayed.

A real-world example

A mid-market professional services firm uses Oracle PeopleSoft to manage procurement, employee records, and finance. The accounting team, project managers, and HR staff collaborate in Google Sheets to track vendor payments, employee allocations, and monthly GL reconciliation, but they manually export PeopleSoft data every Friday and paste it into Sheets, creating version confusion and stale numbers during the week. With Oracle PeopleSoft and Google Sheets connected, the vendor master record, purchase order register, employee directory, and GL summary automatically export to Sheets every Friday night. The team opens Sheets Monday morning with current data already in place, eliminates the manual export step, and can collaborate on the same source of truth. GL reconciliation runs faster because the labor accounts and vendor balances are already pre-populated from the authoritative source.

What you can do

• •Export Oracle PeopleSoft vendors, purchase orders, and invoices to Google Sheets rows, matching by natural key so updates overwrite stale records.
• •Keep an employee directory in Google Sheets synchronized with Oracle PeopleSoft HR records, refreshed on your schedule.
• •Write GL journal entries and account balances from Oracle PeopleSoft finance modules into Sheets for month-end close and reconciliation.
• •Authenticate Oracle PeopleSoft with HTTP Basic Auth or OAuth2 Bearer tokens, and Google Sheets with a service account for server-to-server access.
• •Poll Oracle PeopleSoft on a schedule with date-range filters to reduce load, with retry logic and a full audit trail on every export.

Questions

How does ml-connector handle Oracle PeopleSoft's self-hosted architecture?

Each Oracle PeopleSoft customer operates their own instance with a unique hostname, port, and node name. ml-connector accepts the full REST endpoint URL and credentials per customer, polls that instance for the configured records, and exports them to Google Sheets. Because there is no shared PeopleSoft base URL, the connection is scoped to each customer's deployed environment.

Does Oracle PeopleSoft support webhooks or push notifications?

No. Oracle PeopleSoft has no standardized webhook system for external integrations. The Integration Broker can push XML messages to HTTP endpoints if the customer configures outbound routing, but polling is the recommended approach. ml-connector polls the REST endpoints with date-range filters to fetch only records changed since the last run, balancing freshness with load on the PeopleSoft instance.

What happens if a record fails to write to Google Sheets?

ml-connector logs the failure in the audit trail with the source JSON, the attempted row data, and the error from Google Sheets. Failed records can be reviewed in the audit log and replayed manually or by re-running the flow. If the failure is transient (quota exceeded, network timeout), ml-connector retries with exponential backoff before surfacing the error.