Utility docs
DV Bulk Upsert Runner.
Preview-first Dataverse bulk upsert utility for CSV, JSON, and DVBUR packages. Built for local validation, create/update classification, execution visibility, and actionable failure diagnostics.
What it is
DV Bulk Upsert Runner is a focused DV ForgeLab utility for applying bulk Dataverse data rows through preview-first workflows. It supports CSV imports, JSON imports, and DVBUR package files.
Why it exists
Bulk data application often becomes risky when teams cannot see what will create, what will update, how long execution may take, or which rows failed. DVBUR makes the planned operation visible before Dataverse changes occur.
Typical workflow
Key capabilities
Preview before apply
Imported rows are staged locally. Users inspect records, fields, entity/key selection, warnings, and execution plan before upserts run.
Create / update classification
DVBUR checks Dataverse to determine which rows will create new records and which rows will update existing records where key selection supports classification.
Execution visibility
Long-running operations show processed rows, applied count, failed count, throughput, elapsed time, ETA, and batch progress.
Failure diagnostics
Failures are grouped and summarized with category, column, value, expected type, suggested action, and technical details where available.
Failure review workflow
Users can review failures, export failure rows, and requeue failures for follow-up execution.
Metadata-aware keys
Dataverse metadata helps users understand available primary ID and alternate key options before classification and execution.
Preview-first boundary
DVBUR is a runner, not a migration platform. It applies staged single-entity data rows through controlled upsert workflows. It does not perform ETL, scheduled sync, relationship graph migration, attachment migration, or automatic data cleansing.
Relationship to DV Quick Run
DV Quick Run investigates Dataverse. DV Bulk Upsert Runner applies bulk data changes. Both follow the same ForgeLab principles: summary-first presentation, progressive disclosure, evidence-first workflows, local validation before execution, operational transparency, and no hidden automation.