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ERP Use CasesTier 1Published June 22, 2026

Data Import via CSV / XLSX with Validation and Error Reporting

Data Import via CSV / XLSX with Validation and Error Reporting for US and UK finance teams: ERP requirements, controls, audit evidence, data model, APIs, state transitions, and implementation checks.

Platform - Data Import & Migration is where ERP discipline either begins or breaks.

Data Import via CSV / XLSX with Validation and Error Reporting looks operational from far away. In a real finance team, it is a chain of assertions: the right actor started the work, the required records existed, the control policy was applied, the state change was preserved, and the outcome can be explained later without rebuilding the transaction from emails and spreadsheets.

The expected business outcome is specific: Finance team migrates 5 years of historical data in one day; re-runs produce zero duplicates; non-technical users fix validation errors from the error report without engineer help.

The control flow a finance team actually needs.

Workflow map showing control steps, exceptions, and evidence for this ERP process.CSV And XLSXStart conditionFile Size Limit ...Required checksValidation Repor...Owner and SLAValidation And I...System updateImport Is Idempo...Exception handlingAudit packetEvidence trailException loopPlatform - Data Import & Migration should preserve every override and rejection.
Workflow map for this ERP process, including exception handling and audit evidence.

Step 1

CSV And XLSX

Step 2

File Size Limit ≥50 MB / ≥100,000 Rows

Step 3

Validation Report Returns All Errors In...

Step 4

Validation And Import Are Separate...

Step 5

Import Is Idempotent - Re-Uploading The...

The ERP surface involved.

Module

Platform - Data Import & Migration

Actors

Finance Administrator, Data Migration Specialist, Import Worker

Tier

Tier 1

Finance area

Platform, Integration, Security, Administration & Analytics

Region lens

US and UK finance teams

Publication date

June 22, 2026

Support CSV (RFC 4180) and XLSX (Office Open XML); file size limit ≥50 MB / ≥100,000 rows; validation report returns all errors in a single pass (not fail-fast on first error); validation and import are separate steps requiring explicit user confirmation; import is idempotent - re-uploading the same file produces no duplicate records; failed rows are skippable so partial import is possible; import jobs are async (Temporal workflow) for files >1,000 rows; rollback capability for imports within 24 h of completion; import audit event written per batch.

US and UK teams have different compliance hooks, but the same control problem.

US teams usually care about clean evidence for audit support, vendor records, payment controls, tax reporting, and management review. UK teams usually care about VAT-ready records, approval evidence, digital-record discipline, and traceable postings. The country-specific details differ, but the operating pattern is the same: the ERP needs controlled records, explicit ownership, defensible state changes, and evidence that survives beyond the person who completed the task.

The control matrix.

Control areaRequirementAcceptance proof
Control 1Support CSV (RFC 4180) and XLSX (Office Open XMLGiven a vendor CSV import template
Control 2file size limit ≥50 MB / ≥100,000 rowswhen a user uploads a populated file, then the system runs a full validation pass returning all errors (not fail-fast) before writing any records
Control 3validation report returns all errors in a single pass (not fail-fast on first error
when the user confirms after reviewing validation results, then records are upserted via ON CONFLICT external_id DO UPDATE and re-uploading the same file produces zero duplicates
Control 4validation and import are separate steps requiring explicit user confirmationnegative) when a row references a non-existent account code, then that row appears in the validation report with error code INVALID_REFERENCE and no records from the batch are written until the user confirms partial import or fixes the file.
Control 5import is idempotent - re-uploading the same file produces no duplicate recordsFinance team migrates 5 years of historical data in one day; re-runs produce zero duplicates; non-technical users fix validation errors from the error report without engineer help.
Control 6failed rows are skippable so partial import is possibleFinance team migrates 5 years of historical data in one day; re-runs produce zero duplicates; non-technical users fix validation errors from the error report without engineer help.

Audit evidence is a chain, not a folder.

Evidence layerWhat should be preserved
Business event
Administrator navigates to the import module, selects the data type (vendors, customers, chart of accounts, opening balances, historical invoices), and downloads the template. After populating and uploading the file, the system runs a validation pass: checks required fields, data types, foreign key references (e.g., account codes exist, currency codes are ISO 4217), duplicate external_ids, and money format. A validation report is returned before any records are written. On user confirmation, records are upserted in batches using the ADR-007 ON CONFLICT external_id DO UPDATE pattern. Progress is shown in real time;
failures are listed per row with actionable error messages.
Control rulesSupport CSV (RFC 4180) and XLSX (Office Open XML); file size limit ≥50 MB / ≥100,000 rows; validation report returns all errors in a single pass (not fail-fast on first error); validation and import are separate steps requiring explicit user confirmation; import is idempotent - re-uploading the same file produces no duplicate records; failed rows are skippable so partial import is possible; import jobs are async (Temporal workflow) for files >1,000 rows; rollback capability for imports within 24 h of completion; import audit event written per batch.
Acceptance proof
Given a vendor CSV import template;
when a user uploads a populated file, then the system runs a full validation pass returning all errors (not fail-fast) before writing any records;
when the user confirms after reviewing validation results, then records are upserted via ON CONFLICT external_id DO UPDATE and re-uploading the same file produces zero duplicates;
(negative) when a row references a non-existent account code, then that row appears in the validation report with error code INVALID_REFERENCE and no records from the batch are written until the user confirms partial import or fixes the file.
Data record
import_job { job_id: string, org_id: string, entity_id: string, data_type: enum(VENDORS,CUSTOMERS,COA,OPENING_BALANCES,INVOICES), file_checksum: string, status: enum(VALIDATING,VALIDATION_FAILED,PENDING_CONFIRM,IMPORTING,COMPLETE,ROLLED_BACK), row_count: int, error_count: int, external_id: string };
import_error { job_id: string, row_number: int, field: string, error_code: string, message: string };
(reference, product may differ).
System event
POST /v1/import-jobs { data_type, file: multipart } -> 202 { job_id, status: VALIDATING };
GET /v1/import-jobs/{job_id} -> 200 { status, errors[], progress_pct };
POST /v1/import-jobs/{job_id}/confirm -> 202 { status: IMPORTING };
POST /v1/import-jobs/{job_id}/rollback -> 202;
emits import.validation_complete and import.complete events;
idempotent via external_id on imported records.
Lifecycle state
VALIDATING -> VALIDATION_FAILED | PENDING_CONFIRM -> IMPORTING -> COMPLETE;
terminal ROLLED_BACK;
guard: validation and import are separate steps;
import is idempotent;
rollback available within 24 h of completion.

The useful version of this workflow is not only fast. It is inspectable. A controller, auditor, or operator should be able to move from source event to system record to state transition to final business outcome without guessing.

Implementation contracts.

Reference data model

`import_job` { job_id: string, org_id: string, entity_id: string, data_type: enum(VENDORS,CUSTOMERS,COA,OPENING_BALANCES,INVOICES), file_checksum: string, status: enum(VALIDATING,VALIDATION_FAILED,PENDING_CONFIRM,IMPORTING,COMPLETE,ROLLED_BACK), row_count: int, error_count: int, external_id: string }; `import_error` { job_id: string, row_number: int, field: string, error_code: string, message: string }; (reference, product may differ).

API and events

`POST /v1/import-jobs` { data_type, file: multipart } -> 202 { job_id, status: VALIDATING }; `GET /v1/import-jobs/{job_id}` -> 200 { status, errors[], progress_pct }; `POST /v1/import-jobs/{job_id}/confirm` -> 202 { status: IMPORTING }; `POST /v1/import-jobs/{job_id}/rollback` -> 202; emits `import.validation_complete` and `import.complete` events; idempotent via `external_id` on imported records.

State transitions

`VALIDATING -> VALIDATION_FAILED | PENDING_CONFIRM -> IMPORTING -> COMPLETE`; terminal `ROLLED_BACK`; guard: validation and import are separate steps; import is idempotent; rollback available within 24 h of completion.

Common implementation traps.

Treating the workflow as data entry

If the ERP only stores the final record, the team loses the decision trail that explains how the record became valid.

Hiding exception logic

Exceptions need owners, reason codes, and time stamps. A vague pending state is not a control.

Posting without recovery design

Retries, duplicate submissions, and partial failures must be explicit so the system does not create inconsistent records.

Skipping evidence design

A workflow that cannot produce evidence on demand will eventually push finance teams back into manual screenshots and spreadsheets.

Where Rivane fits.

Rivane is built for finance workflows where automation must stay tied to source documents, approvals, state transitions, ledger impact, reporting, and audit evidence. Use this guide as a checklist for evaluating whether an ERP workflow is merely digitized or actually controlled.

References and source basis.

These sources provide the standards, regulatory, or government context around the flow. They are included so the guide is useful to finance operators, auditors, and implementation teams, not only buyers reading software copy.

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