Data migration with proof that nothing was lost on the way
What’s included
01- ✓Source profiling and field mapping
- ✓Cleaning and deduplication rules
- ✓Row and value reconciliation reports
- ✓Parallel-run validation window
- ✓Rollback snapshots
- ✓Data dictionary handover
The details
02How do you prove nothing was lost?
Row and value reconciliation reports compare the old system with the new one, record type by record type. Row counts show that every customer, item and invoice made the trip; value totals — invoice amounts, stock quantities, outstanding balances — show that the numbers inside them did too. Where the two sides differ, the report shows it rather than rounding it away.
The reports stay with you. When an auditor, your CA or a new manager later asks whether the migration was clean, the answer is a document rather than someone’s memory. That is what moving the data once, correctly, with proof that nothing was lost, looks like on paper.
What happens before anything moves?
Profiling comes first: we look at what is actually in the source, not what the field names suggest — empty columns, dates stored in several formats, the same customer entered more than one way. The field mapping is built from that, so it records where each old field goes, or that it is being left behind.
Cleaning and de-duplication follow rules written down in advance. When two customer records are merged, the rule says which one survives and why, so the result can be checked instead of taken on trust. With dbt in the stack, the rules can be kept as code, so the same clean-up can be run again on the final extract rather than repeated by hand.
What if the new system is wrong after cutover?
The parallel-run validation window keeps the old system running alongside the new one while their outputs are compared: the same invoices, the same stock position, the same balances. Problems surface while the old system can still answer the question, not after it has been switched off.
Rollback snapshots mean that if something does go wrong, the data can be returned to a known state instead of being repaired in place under pressure. The cutover decision is made with the reconciliation reports in front of you, not on a hunch.
Is this the right package, or is a sibling a better fit?
If the move is from one CRM to another, CRM Migration & Cleanup at ₹9,000, delivered within 7 days, is built for exactly that and costs less. This package suits moves where more is at stake: stock and production data, patient or shipment records, or several sources being merged into one.
It is a one-time move, not an ongoing link. Keeping two systems in step afterwards is an integration or a pipeline — Tally Integration & Automation at ₹12,000, or Data Pipeline & Warehouse at ₹1,75,000. Setting up the destination system itself, such as an ERP & Inventory Rollout at ₹1,75,000, is priced separately.
How it works
03- 0115-min callTell us what’s breaking. We ask the questions that change the price.
- 02Scope in writingA fixed quote and a written scope: what’s in, what isn’t.
- 03Build & reviewWorking software early, with review rounds on real screens.
- 04LaunchWe go live with you, train your team and hand over access.
- 05SupportFixes, changes and growth on a retainer, if you want one.
FAQ
04What does data migration cost?
Data Migration & Quality starts at ₹15,000 and is delivered within 30 days. Which systems and which records the price covers is written into the proposal, so there is no doubt later about what was in scope. Your fixed price arrives in writing after a 15-minute scope call.
How long is the parallel run?
Its length is agreed in the proposal. It helps to include an event that exercises the data properly, such as a billing run or a month-end close, so the comparison between old and new covers the work your team depends on most.
Can you migrate out of spreadsheets or an old desktop application?
Tell us on the scope call what you are moving from and to; which systems are covered is written into the proposal. Whatever the source, profiling comes first, so the field mapping is based on what the data really contains rather than on what the old screens suggest.
What is in the data dictionary handover?
A written description of the fields in the new system: what each one means and where it came from in the old one. It is what your team, and any future vendor, will need when a question about the data comes up long after the migration is finished.
Should we clean the data before migrating?
Not as a separate project. Cleaning and de-duplication are part of this package and are applied as the data moves, so you do not pay for a clean-up and then a migration. Carrying years of duplicates into a new system only makes the new system as untidy as the old one.
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