Adaptors / Dynamics 365

Dynamics 365 adaptor

Reusable delivery templates, orchestration patterns, and deterministic validators.

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The Dynamics 365 adaptor covers Finance & Operations and Business Central. It includes data entity mapping templates, staging table orchestration patterns, and deterministic validators for both source extraction and target loading scenarios.

What it accelerates

Faster data entity mapping: pre-built templates for common D365 entities reduce mapping effort
Repeatable staging table loads: orchestration patterns ensure consistent, sequenced imports on every rehearsal
Audit-ready evidence: reconciliation packs with entity counts, validation results, and delta reports
Reduced manual effort: deterministic code-printing replaces hand-coded data migration packages
Dual-platform support: templates for both Finance & Operations and Business Central

How it works with elfware

The controlled non-determinism model applied to Dynamics 365:

1Human decisions: consultants define scope, entity mappings, business rules, and number sequence handling for the D365 environment
2AI-assisted optioning: surfaces mapping choices across data entities and highlights gaps in coverage
3Governed specs: locked decisions become the input to deterministic generation
4Deterministic generation: code-printing produces data packages, staging table scripts, and orchestration from the governed spec
5Deterministic validators: every entity, every field, every relationship checked against governed rules
6Rehearsal and cutover: proven rehearsal chain executed identically each run

AI boundary: AI never processes customer data; it supports mapping and delivery configuration only. When AI assists with code generation, the output is reviewed, QA'd, and verified in test runs before deployment to any system.

Source vs target usage

As a source

Extraction from existing D365 or legacy Dynamics environments for migration to new platforms.

Data entity extraction: standard and custom entities via the Data Management Framework
Financial data: chart of accounts, journals, subledger entries, budgets
Supply chain: purchase orders, sales orders, inventory transactions, warehousing
Product master: released products, variants, categories, attributes
Customer/supplier master: accounts, addresses, contacts, payment terms
History extraction: transactional history with period handling and reconciliation

As a target

Loading data into D365 for new implementations, upgrades, or consolidation projects.

Data entity imports: templates for standard D365 data entity import sequences
Staging table orchestration: sequenced loading respecting entity dependencies
Number sequence management: handling of number sequences during migration to avoid conflicts
Configuration migration: system parameters, organisation structures, legal entities
Reconciliation: post-load validators confirm data integrity across all imported entities

Typical artefacts delivered

Mapping templates

Pre-built source-to-target mapping documents covering D365 data entities with transformation rules, defaults, and exception handling.

Orchestration / run groups

Sequenced import plans ensuring entity dependencies are respected (e.g., products before inventory, customers before orders).

Deterministic validators

Automated checks for entity constraints, referential integrity, number sequence consistency, and business rule compliance.

Reconciliation / evidence pack

Entity counts, field-level validation results, and balancing reports providing audit-ready sign-off evidence.

Cutover rehearsal playbook

Step-by-step runbook for D365 migration rehearsal including environment preparation, timing, and rollback procedures.

Interfaces and data domains

Domain	Typical entities	Cadence	Notes
Products	Released products, variants, categories, attributes, bar codes	Full + delta	Posting group and UoM referential integrity plus history window
Customers	Customer accounts, addresses, contacts, payment terms, credit limits	Full + delta	Payment terms, posting group, and VAT reg format rules
Suppliers / vendors	Vendor accounts, addresses, contacts, payment terms, purchase agreements	Full + delta	Purchaser code and posting group referential integrity
Financials	Chart of accounts, journals, subledger, budgets, dimensions	Full + history	Period handling critical plus history window
Inventory / balances	On-hand inventory, warehousing, batch/serial tracking, reservations	Snapshot at cutover	Cutover timing dependent
Sales	Sales orders, sales lines, returns, delivery schedules	Open + history	Customer and item referential integrity plus history window
Purchasing	Purchase orders, purchase lines, receipts, invoices	Open + history	Vendor and location referential integrity; item-UoM cross-reference plus history window
Reference data	Units, currencies, number sequences, organisation hierarchies	Full	Foundation dependency

Common risks and how we mitigate them

Data entity version differences

Adaptor templates are version-aware, with logic that handles field changes between D365 releases and update waves.

Number sequence conflicts

Migration templates include number sequence gap analysis and reservation patterns to prevent conflicts post-go-live.

Entity dependency ordering

Orchestration enforces correct import sequencing based on D365 entity dependency maps, validated at each rehearsal.

Dual-write and integration conflicts

Cutover playbook includes integration pause/resume steps to prevent dual-write conflicts during migration windows.

Financial period and dimension handling

Validators check period assignments, dimension combinations, and subledger consistency for all financial data.

Custom entity handling

Adaptor supports custom data entities alongside standard ones, with validators extended to cover custom fields and relationships.

Frequently asked questions

What do you need to start?

Access to the D365 data model or data entity documentation, clarity on which modules are in scope, and the target environment details. We can work from export samples and documentation initially.

How long to first prototype?

Typically 2 to 3 weeks from kick-off to a working prototype demonstrating data entity mapping, staging table loading, and reconciliation for a representative domain.

How do validators reduce risk?

Validators check every record against the D365 data entity constraints, referential integrity rules, and business logic before import. They run on every rehearsal and produce objective pass/fail evidence.

Do you support history builds?

Yes. The adaptor supports progressive history builds for transactional data including sales orders, purchase orders, and financial journals with effective dating and period handling.

How do adaptors evolve over time?

Each D365 engagement adds new entity mappings, validators, and orchestration patterns. These are folded back into the reusable library for future programmes.

Do you cover both Finance & Operations and Business Central?

Yes. The adaptor includes templates for both platforms, with variant handling for the different data entity structures and integration patterns.

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