Services

Data Migration

Moving a data platform is high-stakes. Schema changes break downstream consumers, ETL refactors take longer than planned, and cutover windows are short. We have run enough of these to know where the risk hides and how to sequence the work so the business stays operational throughout.

Talk to us about data migration Related case studies

What's included

Three things we focus on.

Assessment and planning

Catalog the source environment, map dependencies, identify the fragile spots, and produce a migration plan with realistic timelines and a risk register before a single row moves.

Migration execution

Schema conversion, data movement, pipeline re-platforming, and consumer validation done in phases. Parallel-run periods built in so there is a proven rollback path at every stage.

Cutover and stabilization

Cutover weekend planning, go/no-go criteria, hypercare period, and post-migration monitoring until the new platform is operating normally under production load.

How we engage

Whatever shape fits the work.

Migration assessment

Two to four weeks. Full inventory of the current environment, migration complexity scoring, and a sequenced plan with effort estimates.

Phased migration

Execute the migration in defined phases with parallel runs and sign-off gates between each stage.

Full delivery

End-to-end accountability from assessment through cutover and hypercare. One team, one contract.

Common use cases

What we get asked to do.

Migrate on-prem SQL Server to Azure SQL or Azure SQL Managed Instance
Move an on-prem data warehouse to Azure Synapse Analytics
Re-platform SSIS ETL pipelines to Azure Data Factory during a migration
Migrate Oracle or DB2 workloads to Azure SQL with schema conversion
Conduct a pre-migration assessment and complexity scoring of a data estate
Execute a parallel-run validation period before production cutover
Recover a stalled or failed data migration and produce a corrective plan
Migrate a reporting environment to a new data platform with consumer validation

Why Nextekk

What we bring to data migration.

We have rescued stalled migrations

Nextekk has been brought in to recover data migration projects that broke production or stalled. We know where the risk hides: schema edge cases, consumer coupling, ETL timing assumptions. We have seen them fail.

Parallel-run discipline

We do not cut over until the new environment has been running under production load in parallel with a verified rollback path. Cutover weekend is boring when the migration is done right, and boring is exactly what we are aiming for.

Consumer validation as a deliverable

The migration is not complete when the data moves. It is complete when the downstream teams (reporting, applications, data science) have confirmed their numbers match. Consumer sign-off is a milestone, not an afterthought.

Hypercare after cutover

The week after cutover is when migrations break. We stay engaged with active monitoring and rapid-response support through the hypercare period rather than handing the keys over and disappearing at go-live.

Business value

What clients typically see.

99.9% data fidelity standard on all Nextekk migrations, validated through consumer sign-off before cutover

Zero unplanned downtime on completed Nextekk migrations that followed the parallel-run discipline

30% under initial estimate on average for migrations that begin with a thorough assessment and dependency map

3-4x longer actual migration timelines vs. initial vendor estimates when dependency and consumer complexity is not mapped upfront

Ready to talk about data migration?

Tell us what you are trying to change. We will either be useful, or point you to who would be.

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