A migration control layer over the Dynamics 365 Finance & Operations data management framework: templates, dependency ordering, dry-run validation and reconciliation. Built to order for your cutover. Built to order by ECOSIRE for Dynamics 365 F&O (build-to-order) — indicative price from $1199.00 USD; request a quote for a scoped proposal.
A migration control layer over the Dynamics 365 Finance & Operations data management framework: templates, dependency ordering, dry-run validation and reconciliation. Built to order for your cutover.
Built to order
Go-live data loads fail in a predictable order. Customers import before payment terms exist. Items import before the storage and tracking dimension groups are set up. Open receivables import before customers. Somebody runs the target step at two in the morning, twelve thousand rows land in staging, four thousand of them error, and the error text points at a field that was never in the source file. The load is re-run from scratch because nobody can safely re-run only the failures, and by the third attempt the cutover window has gone.
The failure is almost never the data management framework itself. DMF moves data reliably. What projects lack is the layer above it: an ordered plan, templates that match the entity metadata for the version actually deployed, a way to validate rows against real target configuration before the target step touches a table, a stable mapping between legacy keys and F&O records, and a reconciliation report that a controller will sign.
The Data Migration Workbench is that layer, built to order by ECOSIRE for your programme. It is not a replacement for DMF and does not bypass it — it drives DMF data projects, staging tables and batch execution from a plan you can rehearse, measure and repeat.
Migration waves are records in F&O. Each wave names its legal entities, its entity list, its cutover window and its owner. Within a wave, the workbench derives execution units, levels and sequences from a dependency graph of the data entities in scope, so masters precede transactions and prerequisites precede dependants without anyone remembering the order. The generated DMF data projects are standard, inspectable and runnable outside the workbench if you ever want to.
Source templates are produced from the entity metadata in the environment you are loading — field list, data types, mandatory flags, enum values and the fields your extensions added. That removes the most common time sink on a migration: a template built from documentation for a different version, filled in by a business team over three weeks, then rejected wholesale on import.
Rows land in staging and are then validated against live target configuration: does the customer group exist, is the financial dimension value valid and active for that ledger, does the number sequence have capacity, is the item's tracking dimension group compatible with the on-hand rows that follow, are dates inside open fiscal periods. Failures are reported per row with a cause and a suggested correction, before a single record is written to the target. A dry run can be executed repeatedly against a refreshed sandbox without touching production.
Field-level transformation rules — defaulting, lookup translation, concatenation, trimming, unit and currency conversion — are configured per entity rather than buried in per-file spreadsheet formulas that nobody can reproduce at cutover. Every record created is written to a cross-reference table linking the legacy identifier to the F&O key, which is what makes the subsequent transaction loads, and the eventual audit question of where a balance came from, answerable.
For each wave and legal entity, the workbench reports source count and control totals against staged rows against records created in the target, with the differences itemised rather than summarised. Opening balance loads — general journal lines, open customer and vendor invoices, on-hand quantities — get their own reconciliation showing the resulting trial balance, aged AR and AP, and inventory value against what the source system said, so the sign-off conversation is about a report rather than a promise.
Staging errors are grouped by cause, not listed by row, so one missing setup record shows as one problem affecting 900 rows instead of 900 problems. Corrections can be applied in staging and only the failed rows re-run. A wave can also be reversed and reloaded cleanly where the entity supports it, which is what makes rehearsal realistic.
Execution runs on the SysOperation batch framework with recurrence, parallel task limits and a stop-on-critical-failure rule, so a long load can run overnight without a person watching it. A workspace shows wave progress, throughput, current step, elapsed time against the rehearsal baseline, and the open error count — the numbers a cutover manager needs at 4am to decide go or no-go.
Implementation programmes moving from a legacy ERP, from spreadsheets, or from another Dynamics 365 estate onto F&O; groups adding a new legal entity to an existing production environment; and teams facing repeated data loads such as annual acquisitions or periodic master data refreshes. It is equally useful to a partner who runs several F&O implementations a year and wants the same rehearsal discipline on each.
1. Scoping call. We review your source systems, the entity list in scope, legal entity structure, expected volumes, your F&O version and how many rehearsals you plan. 2. Fixed quote. A written scope lists every entity, transformation rule and reconciliation report included, plus assumptions about source data quality. Extra entities are quoted as additions. 3. Build. Development as X++ extensions in a dedicated model, with the dependency graph and templates generated against your environment's metadata. 4. Install in test. The deployable package goes into your sandbox through your LCS pipeline. We run at least one full dry run with your real extract and work through the errors with your team. 5. Production. The same package is promoted through your normal release process for the cutover, and we are available during the live load window. 6. Support. A defined support window follows go-live for defects and configuration questions, and can be extended to cover later waves.
ECOSIRE builds this for you on request. There is no instant download, no free trial, and typical lead time is two to four weeks from an agreed scope. The workbench does not clean your source data, invent missing master records, or make a decision about what your opening balances should be. It makes those decisions visible early, enforces them consistently, and proves the result — which is the difference between a cutover that finishes and one that gets extended.
A short call to confirm the workflow, your platform version and where the integration boundaries sit.
You receive a written scope and a fixed price. Nothing is built until you approve it.
We develop against a copy of your configuration and test it there. Typically two to four weeks.
We install on your instance, hand over the source, and support it for twelve months.
Spends the run-up to cutover rebuilding templates and chasing errors that all trace back to one missing setup record. Generated templates, dependency ordering and cause-grouped triage turn a three-day reload into a re-run of the failed rows.
Has to give a go or no-go on the cutover night with no objective measure of whether the load is on track. The wave workspace shows progress against the rehearsal baseline and the open error count, so the decision is based on numbers rather than optimism.
Is asked to sign off opening balances they cannot tie back to the legacy trial balance. Per-entity reconciliation of source totals, staged rows and posted results — plus a cross-reference from every F&O record to its legacy key — makes that sign-off defensible.
| Criterion | ECOSIRE | Custom Build | Competitor |
|---|---|---|---|
| Automatic dependency ordering of data entities into execution units and levels | Included | Partial support | Partial support |
| Templates generated from live entity metadata including extension fields | Included |
From $1199.00
Starting point — quoted to your scope
| Partial support |
| Dry-run validation against target configuration before the target step runs | Included | Not included | Partial support |
|---|
| Legacy-to-F&O key cross-reference retained for audit and downstream loads | Included | Partial support | Partial support |
|---|
| Re-run of failed rows only, without reloading the whole wave | Included | Not included | Partial support |
|---|
| Per-entity reconciliation of source, staged and target totals for sign-off | Included | Not included | Partial support |
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| Runs entirely on standard DMF projects and the batch framework | Included | Partial support | Partial support |
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| Source code delivered so the tool is reusable after go-live | Included | Included | Not included |
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