Stabilizing and Scaling Spobik
Turning a slow e-commerce site into a fast, secure revenue-generating platform
Key Results:
- 6x faster load time (600 ms → 38 ms)
- Updates for 500,000+ items in ~10 min
- Largest Contentful Paint: 0.24 seconds
A migration fails quietly. Records land in the wrong field, totals stop matching, and the business finds out weeks later. Forbytes maps your data first, validates it at every stage, and moves it with a rollback point in place before the first record leaves the old system.
| Data Migration Benefit | Business Impact |
|---|---|
| Full data audit and mapping | You know what exists, what is duplicated, and what is safe to drop |
| Validated migration | Record counts and totals match on both sides before you switch |
| Preserved historical data | Year-over-year reporting survives the move |
| Cloud or warehouse target | Storage scales with volume instead of hardware purchases |
| Cleaned and deduplicated data | The new system starts without inherited data quality problems |
| Documented rollback plan | A failed step reverses instead of turning into an outage |
Data Audit & Source MappingInventorying every source, its volume, its owner, and the quality problems already inside it.
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#2
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Migration Plan & Rollback DesignSequencing the move, setting the cutover window, and defining the rollback points.
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#4
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Validation & ReconciliationComparing record counts, totals, and samples until the numbers agree.
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#6
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#1
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Target Design & Mapping RulesDefining the target structure, field-level mapping, and transformation rules.
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#3
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Trial Data Migration & TestingRunning the full migration on a copy, measuring duration, and fixing what the dry run exposes.
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#5
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Cutover & Post-Migration SupportSwitching over, monitoring the first production days, and decommissioning the old system.
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Group Manager, Guesty
CIO at AB Stenströms Skjortfabrik
CEO at The African Touch
A migration project covers the full move: auditing and profiling the source data, designing the target structure, writing field-level mapping and transformation rules, cleaning and deduplicating, running trial migrations, validating the results against the source, executing the cutover, and supporting the first production weeks. We handle database, application, cloud, and full infrastructure migrations, including moves from on-premises systems to Azure, AWS, or Google Cloud.
Migration is a one-time move with an end date: data leaves one system and lands in another, and the old system gets retired.
Data integration is permanent plumbing: pipelines that keep running so several systems stay in sync. Projects often need both, since data usually arrives in a new platform that then has to exchange information with everything else. We scope them separately so you can see what each one costs.
For most projects, minutes rather than hours. The bulk of the data moves while the old system stays live, then a final delta sync runs inside the cutover window. Zero-downtime migrations are possible where the source system supports change data capture, though they cost more and add complexity, so we recommend them only when the business genuinely cannot pause.
Each stage has a defined rollback point, and the trial migration is where most problems surface, which is exactly why it exists. If validation fails after the cutover, the old system is still intact and reachable until we agree it can be decommissioned. Decommissioning is a separate decision made after the new system runs clean, never on cutover day.
Yes, and this is common with systems that outlived the people who built them. We profile the data directly to reconstruct the actual structure, spot the fields that are used in ways the schema does not suggest, and confirm the rules with the people who work in the system daily. It adds time to the audit stage, and we scope that stage separately so the estimate does not rest on guesswork.