Data migration services
The migration is where most rollouts quietly fail, and the usual cause is old data that was dirty in ways nobody documented. Blank email fields. Duplicate phone numbers entered three different ways. Invoices with zero values. Foreign keys pointing at deleted records.
What's included in Migration services.
We migrate in four passes: sample, validation, rehearsal, go-live. Each pass surfaces a new layer of data weirdness. By the time go-live runs, the surprises are gone.
Any team replacing an existing system where data continuity matters: moving off a legacy CRM, replacing Tally, retiring a shared-Excel register, consolidating multiple branch systems. Especially good when nobody currently 'owns' the data quality.
- 01
Source assessment
First-day walkthrough of the source system to identify the worst data hotspots, usually contacts, addresses, and old invoice records.
- 02
Sample migration
First 5% of records pulled, transformed, loaded. Visible in the new system early, so your team can catch field mapping mistakes before the full load.
- 03
Validation pass
Full data pulled, QA scripts run for duplicates, blanks, formatting issues, broken references. Outputs a 'fix-list' for the source team or a defaults policy for the import.
- 04
Rehearsal cutover
Full cutover dry-run ahead of go-live, against a staging environment. Reveals the operational issues: login flow, exports, integration triggers.
- 05
Go-live cutover
Final cutover with a written playbook, named owners per step, rollback procedure, and a 'go/no-go' checkpoint at each stage. Usually a Saturday morning.
- 06
Post-cutover reconciliation
Side-by-side count and value reconciliation between source and new system, with sign-off from finance before old system is decommissioned.
From dirty source data to a clean cutover.
Assess the source data
We walk through the source system or spreadsheets with the people who maintain them and find where the data is weakest: blank fields, duplicates entered different ways, references to deleted records. Field mappings, cleanup rules and who fixes what at source are agreed in writing.
Sample, validate, rehearse
We load a small sample first so your team can check the field mappings, then run QA scripts across the full dataset and produce a fix-list. A complete dry-run in a staging environment shows how logins, exports and integrations behave after cutover.
Cut over and reconcile
We run the real cutover from a written playbook with named owners, a rollback path and go or no-go checkpoints. Record counts and values are then reconciled side by side, and the old system stays available until finance signs off.
Questions about Migration services.
- How do we move years of data out of shared Excel sheets into a new system?
- In four passes: sample, validation, rehearsal and go-live. We begin with a walkthrough of the source files to find the worst hotspots, usually contacts, addresses and old invoice records. The first 5 percent of records is loaded early so your team can catch field mapping mistakes, and each later pass surfaces a new layer of problems, so the surprises are gone by the time the real cutover runs.
- Can you migrate data from Tally, SAP Business One, Salesforce or HubSpot?
- Yes. Those are common sources, along with shared Excel registers and separate branch systems being consolidated into one. Data is extracted into a PostgreSQL staging area, transformed with custom ETL written in Node.js, and checked with QA scripts for each entity before it reaches the new system. When a source system is being replaced, it is not decommissioned until the figures are reconciled and finance signs off.
- What happens to duplicates, blank fields and broken records during migration?
- They are found before go-live. The validation pass pulls the full dataset and runs QA scripts for duplicates, blanks, formatting problems and references that point at deleted records. The output is either a fix-list for your team to correct at source or a defaults policy for the import, and we agree with you which applies to each issue before the full load runs.
- How do you make sure nothing is lost at cutover?
- We rehearse it first. A full cutover dry-run against a staging environment exposes operational issues such as login flow, exports and integration triggers. The real cutover follows a written playbook with named owners per step, a rollback procedure and a go or no-go checkpoint at each stage. Afterwards we reconcile record counts and values side by side between the old and new systems, and finance signs off before the old system is decommissioned.
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Tell us what's slowing you down.
A 30-minute discovery call. We map the process, point out the easy wins, and outline a clear plan (no obligation).