Source Profiling
Measure volumes, uniqueness, missing values, relationships and known exceptions before relying on a field mapping.
SALESFORCE MIGRATION & UAT
Move the data without losing control of the operation
We keep migration decisions, load state, reconciliation and user acceptance testing connected, so the business can understand what moved, what changed and what remains before cutover.
A REPEATABLE MIGRATION PATH
Every Stage Leaves Evidence For The Next Decision
Migration risk is easier to assess when the process can explain what it received, what it changed, what it loaded and what still needs attention.
When This Service Fits
- Replacing a legacy CRM or operational database
- Separating a business or customer data set
- Combining Salesforce orgs after organisational change
- Migrating complex recurring-revenue data through phased loads and UAT
- 01 Profile Source shape, quality and volume
- 02 Map Target field and treatment decision
- 03 Transform Versioned, repeatable scripts
- 04 Load Controlled sequence and state
- 05 Reconcile Counts, relationships and exceptions
- 06 UAT Business scenarios and evidence
- 07 Release Cutover decision and support route
WHAT WE DELIVER
Data Engineering And Business Acceptance, Kept Together
For legacy replacements, business carve-outs, org consolidations and phased migrations, the technical load is only one part of the work. We connect mapping decisions, scripted treatment, UAT findings and release readiness so the business can understand what will change.
Field Mapping & Treatment
Record whether each source value is preserved, transformed, defaulted, derived, held for review or deliberately excluded.
Scripted Transformation
Use versioned scripts and configuration for repeatable changes instead of manual spreadsheet edits that cannot be reproduced.
Controlled Loading
Sequence records and relationships, retain identifier crosswalks and make the state of each load explicit before any rerun.
Reconciliation & Exceptions
Compare expected and actual results, inspect relationship integrity and route unresolved rows to an owned decision.
UAT & Cutover
Prepare business scenarios, triage findings, validate fixes and bring migration evidence into the go-live decision.
CONTROLLED RERUNS
Know The Current State Before Running Anything Again
Migration scripts need explicit recovery behaviour. A rerun that was safe in an empty test org may be destructive after users have added fresh data or another load has completed.
- Checkpoint the stateRecord which source snapshot, script version and load stage produced the current Salesforce data.
- Separate reset from loadMake destructive preparation an explicit, reviewed action rather than a hidden side effect of rerunning a script.
- Preserve crosswalksRetain source-to-target identifiers and parent-child dependencies so repeated stages can reason about existing records.
- Choose the recovery routeDecide whether to resume, correct, reload a bounded set or restore from a known point based on the evidence in front of the team.
TRACKER TO RELEASE
Turn UAT Feedback Into A Controlled Fix
A shared tracker gives business testers a clear place to record the scenario and evidence. Technical findings then move into source-controlled delivery, while status and retest guidance return to the same business-facing record.
Scenario & Evidence
Capture the record, user, expected result, actual result and supporting screenshot or export.
Migration Or Product Decision
Separate data-treatment defects from configuration, code, training and new-scope requests before fixing anything.
Linked Technical Change
Create a focused issue and branch when the finding requires scripts, metadata or code to change.
Retest & Closure
Return the deployed fix, environment and retest steps to the tracker, then close only when the outcome is accepted.
RECONCILIATION EVIDENCE
Answer More Than “Did The Load Finish?”
A completion decision needs evidence that the expected records and relationships arrived, deliberate exceptions are understood and the resulting operation behaves as intended.
| Control area | Evidence | Decision supported |
|---|---|---|
| Volume | Source, transformed, loaded, held and failed counts | Whether every source row has a known treatment |
| Identity | External identifiers, duplicates and source-to-target crosswalks | Whether records can be traced and safely related |
| Relationships | Parent-child links, orphan checks and dependency results | Whether the migrated lifecycle remains connected |
| Business rules | Representative scenarios, calculated values and exception review | Whether the target behaves correctly for real operations |
| Release | Open defects, accepted exceptions, cutover steps and named owners | Whether the remaining risk is understood and accepted |
WHAT THE BUSINESS CAN SIGN OFF
A Migration The Business Can Explain And Operate
UAT Findings Stayed Connected To The Migration State
We used scripted transformations, explicit load-state tracking and a shared UAT issue log across a complex Salesforce migration. Findings were separated into data treatment, product behaviour and new scope before changes were made, while rerun decisions accounted for records already created during testing.
Reproducible Treatment
Mapping and scripted transforms show how source data became the Salesforce result.
Visible Exceptions
Held, failed and deliberately excluded records have an owner and a recorded decision.
Operational Acceptance
UAT provides evidence that the migrated data supports the customer lifecycle rather than treating row counts as the whole result.