Source-to-Target Traceability
Document where values came from, how they changed and which target fields receive them.
DataConsultant helps organisations move customer, product, supplier, location, material and other master or reference data into a governed target environment without treating migration as a simple record-copy exercise. The engagement connects source profiling, mapping, cleansing, duplicate resolution, hierarchy and reference-data alignment, test loads, reconciliation, cutover and stewardship handover.
Timeline and commercial terms are confirmed after reviewing the master-data domains, source systems, target platform, record volumes, data quality, mapping complexity, test cycles and cutover requirements.
Document where values came from, how they changed and which target fields receive them.
Make data owners and stewards part of material mapping, merge and exception decisions.
Validate the migration repeatedly before production and define evidence for business acceptance.
Transfer rules, exceptions, runbooks and ownership so the target master remains governed after cutover.
Master data sits inside operational processes, analytics, controls and customer or supplier interactions. A migration can fail even when records technically load if identities, hierarchies, business rules or ownership are not preserved.
Use a structured migration approach when the target environment needs trusted master data from fragmented, duplicated or differently structured sources.
MDM data migration is a controlled process for moving and reconciling master and reference data into a target master-data environment or governed business application. It combines technical migration with business rules for identity, ownership, quality, reference values, hierarchies and acceptance.
A complete migration may therefore involve more than extraction and loading. It can require source profiling, canonical mapping, standardisation, duplicate resolution, survivorship, exception workflows, staging, repeatable test loads, reconciliation, cutover planning and post-load validation.
Share the source systems, target platform, priority domains and known data-quality problems. DataConsultant can help frame the profiling, mapping, ownership and decision work needed before migration build or cutover.
The exact scope is tailored to the target platform, migration risk and client delivery model. These capability areas show the main controls a material master-data migration may need.
Inventory source systems, entities, volumes, key fields, data conditions and known constraints.
Define which entities, records, history, attributes and migration waves are in or out of scope.
Map keys, attributes, data types, relationships and required target structures with accountable approval.
Prepare formats, values and mandatory attributes so target rules can be applied consistently.
Define identity resolution, duplicate criteria, review thresholds and survivorship decisions.
Crosswalk code sets and parent-child structures while controlling deprecated and unmapped values.
Design repeatable extraction, staging, transformation, loading, error capture and reprocessing paths.
Validate completeness, integrity, business rules, relationships and acceptance criteria through test cycles.
Sequence production migration, dependencies, checkpoints, go/no-go decisions and feasible fallback actions.
Validate production results, transfer exceptions and document ownership for ongoing stewardship.
Material migrations should be rehearsable. The delivery sequence below keeps mapping decisions, quality controls, test evidence and cutover ownership connected from discovery through stabilisation.
Confirm target, domains, scope, sponsors, success criteria, constraints and delivery responsibilities.
Assess source structures, values, duplicates, relationships, reference data and quality conditions.
Approve mappings, transformations, matching, survivorship, hierarchy and exception rules.
Implement or support staging, extraction, transformation, load sequencing and error handling.
Run controlled test migrations, reconcile outcomes, resolve exceptions and repeat where required.
Execute approved steps, monitor control points, reconcile results and support go/no-go decisions.
Validate production data, close or transfer exceptions, document outcomes and hand over controls.
The service is useful when master-data movement is tied to platform change, consolidation or new enterprise ownership—not only a one-off file import.
Prepare and migrate existing masters into a new hub or registry while preserving identity, mappings and stewardship decisions.
Resolve overlapping customer, supplier, product or location records across acquired and existing systems.
Convert master and reference data into target structures that support redesigned business processes and integrations.
Map legacy organisational, product, geographic or classification structures into controlled target hierarchies.
Bring multiple source identities into governed master records with matching, survivorship and exception handling.
Add a new master-data domain or source system to an established MDM environment with controlled mappings and acceptance.
Bring the problem domains and target model. DataConsultant can help structure the rule decisions, exception paths, reconciliation evidence and ownership needed for a migration that business teams can validate.
Outputs are adapted to the agreed delivery model. Advisory-only engagements may focus on strategy and specifications, while implementation scope can add pipelines, load procedures, test execution and cutover support.
Domains, sources, target, record scope, waves, assumptions, dependencies, owners and exclusions.
Entity structures, volumes, keys, relationships, quality findings and evidence limitations.
Source-to-target attributes, data types, transformations, keys, relationships and approvals.
Duplicate criteria, confidence thresholds, merge rules, precedence and exception treatment.
Legacy values, target codes, effective dates, mappings, parent-child rules and exceptions.
Where implementation is in scope: extraction, staging, transformation, load and error-handling assets.
Test cases, control totals, business rules, exception evidence, acceptance status and sign-off inputs.
Sequence, dependencies, checkpoints, roles, validation steps, issue paths and fallback decisions.
Material defects, ownership, severity, remediation action, acceptance status and residual risk.
Operational ownership, retained rules, exception handling, monitoring needs and knowledge transfer.
Inputs do not need to be perfect, but missing evidence should be visible. Migration decisions are stronger when business owners, stewards and technical teams can validate the meaning of the data rather than leaving every choice to the migration script.
MDM migration frequently involves business-critical or personal information. The migration design should define who can access it, who approves material decisions, how changes are evidenced and how exceptions are carried into operational stewardship.
Assign accountable data owners and stewards for mappings, exceptions, merge decisions and acceptance.
Align access, secure transfer, environment separation, logging and sensitive-data restrictions to project requirements.
Retain mappings, transformation logic, source references and exception evidence needed to explain material outcomes.
Define validation rules, tolerances, control totals and conditions for acceptance or escalation before cutover.
Coordinate freezes, deltas, dependencies, go/no-go decisions, contingency actions and post-load checks.
Use the engagement to make reconciliation criteria, migration rehearsals, business sign-off, exception ownership, cutover sequencing and post-load checks explicit before production data is moved.
A different service may be more appropriate when the need is only infrastructure movement, a small one-off import or a broader governance programme with no immediate migration.
A fixed public fee is not published for this service. A defensible proposal depends on the data domains, migration architecture, quality condition, decision workload and cutover support required.
Public prices for general data migration or software onboarding are not sufficiently comparable to establish an accurate enterprise MDM migration fee. DataConsultant therefore uses scope-led pricing rather than presenting an unsupported market average.
The proposal can separate advisory, migration implementation, assurance and cutover support where that helps procurement and delivery governance.
Request a Scoped MDM Migration ProposalThe service connects governance and migration engineering so business definitions, ownership and controls remain visible while technical migration work is designed and executed.
Keep domain owners and stewards involved in material mappings, duplicate resolution, exceptions and acceptance.
Translate master-data rules into migration specifications, test criteria and operational handover rather than separate documents.
Use profiling, test loads, reconciliations and documented limitations to support informed migration decisions.
Work with the selected MDM and application landscape without forcing a predetermined software answer.
Document rules, runbooks, exceptions and responsibility boundaries so migration knowledge remains usable after cutover.
Share your target platform, domains, source systems, data condition and cutover objective. DataConsultant can structure a proposal around the migration decisions and delivery responsibilities that are actually required.
Answers to common enterprise questions about scope, duplicate resolution, mapping, testing, cutover, platforms, security, duration, pricing and delivery responsibilities.
Share your contact details and requirement. DataConsultant can review the likely scope, evidence, stakeholders, migration controls and appropriate next step.