Epicor DMT Data Load Time Calculator
Cutover weekends fail when the data load runs longer than the window. This calculator turns record counts and a measured DMT speed into a realistic effort figure, including the rework that clean-looking files still generate.
Your numbers
Total rows across the DMT files in this load.
Measure on a 500 row test file in your environment.
Analyse the message, correct the source cell, save the file.
Open, map, validate, and archive logs.
Your results
Planning estimate. Throughput varies with entity, triggers, BPMs and server load. Always rehearse the load in a copy of production.
Total effort vs first pass error rate
Sweeps Error rate on first pass from 0 to 30, holding your other inputs fixed.
Migration load plan review
Optional: share your cutover plan and we will review the load sequence and rehearsal approach.
Optional. The tool and every export work without this. No spam.
How to use it
Count the records in each load, then time a small test file to get records per minute. Enter your first pass error rate from earlier rehearsals, the average time to fix an error and the number of records per file. The result splits machine load time, rework and per-file overhead, then adds verification time so you can size a cutover window.
- Load order matters: reference data, parts, customers, then transactions.
- Re-run the estimate after each rehearsal with the real error rate.
- Use the chart to see how much cleansing before the load is worth.
The formula
Load time is records divided by speed. Errors equal records times the error rate. Rework is errors times the fix time plus the time to reload those errors at the same speed. Overhead is the number of files times the per-file handling time. Total hours add all three, converted from minutes, plus verification. The model ignores parallel loading, which can shorten wall-clock time when entities do not depend on each other.
Reading the chart
The sweep shows effort rising almost linearly with the error rate, because each error costs human time rather than machine time. That is why data cleansing in the source spreadsheet usually beats faster hardware. If a few percentage points of errors add a full working day, invest in validation formulas and lookup checks before running DMT.
Common mistakes
Teams measure speed on an empty test company and assume it holds in a full one with BPMs, UD triggers and big indexes active. Others forget attachments, multi-company loads and sign-off time. Plan for at least one full dress rehearsal and keep the DMT logs so you can fix patterns, such as one bad unit of measure, in bulk.
Frequently Asked Questions
What is a realistic DMT speed?
It varies widely by table and by triggers. Simple masters may load quickly, while transactional tables with BPMs are slower. Always measure with a sample file in your own environment rather than trusting a rule of thumb.
Can I run several DMT sessions in parallel?
Often yes for independent entities, which reduces elapsed time though not total effort. Avoid parallel loads that touch the same records or depend on each other, and watch database locking.
Why add a verification step?
A load that finishes without errors can still be wrong. Reconcile counts and totals against the source, such as on-hand quantity and open order value, before declaring the load complete.
Does this cover Epicor Kinetic cloud?
The arithmetic is the same, but cloud tenants may restrict how and when large loads run. Confirm limits and scheduling with your Epicor cloud contact when planning the window.
If you need to script or accelerate migrations into Epicor, Netray can help design the validation and load pipeline. The calculator is free either way.
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