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IBM · IBM SPSS Statistics → Amazon SageMaker · Migration

Your Trusted SPSS to SageMaker Migration – Fixed Scope, Senior Engineers

Migrating IBM SPSS Statistics to Amazon SageMaker is a well-understood project. Our senior engineers handle proprietary exports, data migration to S3, and model conversion with a fixed scope and timeline.

Get My Free AssessmentA 2-hour architecture review led by senior engineers. No commitment.

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A 2-hour architecture review led by senior engineers. No commitment.

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Powered by the 3PS Migration Engine

The lowest-cost way off IBM SPSS Statistics: our migration tooling automates the repetitive work —you pay senior engineers for judgment, not keystrokes.

Automated discovery
Your IBM SPSS Statistics estate mapped — workloads, dependencies, licensing — before day one
Conversion tooling
Schema, config and workload translation to Amazon SageMaker, automated where it's safe
Parity validation
Side-by-side testing proves Amazon SageMaker matches production before cutover
Runbook cutover
Rehearsed, reversible, scheduled in your maintenance window
4–7 months
Typical project timeline
$100k–$550k
Fixed budget range
40–70%
Savings on legacy support

How we support IBM SPSS Statistics → Amazon SageMaker after migration

  • Senior platform engineers lead every migration.
  • Fixed scope – no surprise overruns or delays.
  • 40-70% savings on legacy support while you plan.
  • 24/7 US-based support during and after migration.
  • Proprietary SPSS models and data migrate cleanly.
  • Post-migration MLOps, cost optimization, drift monitoring.

Cloud mandate vs. legacy lock-in

Corporate cloud mandates and data center exits require moving SPSS workloads to AWS SageMaker, but the proprietary export formats and on-prem data sources make it complex.

Rising licensing costs

High SPSS licensing costs block team growth. You need a cost-effective path to SageMaker without disrupting operations.

Missing modern MLOps

Your team demands modern MLOps, APIs, and microservices—capabilities SPSS on-prem can't deliver. Migrating to SageMaker unlocks them, but the migration itself feels risky.

IBM SPSS Statistics → Amazon SageMaker migration — your questions answered

How do you migrate from SPSS to SageMaker?+

Yes—migrating IBM SPSS Statistics to Amazon SageMaker is a well-understood project. Our engineers handle proprietary neural network and decision tree exports, data migration to S3, and model conversion. Timeline: 4–7 months, budget $100K–$550K, fixed scope.

What about SPSS-proprietary model formats?+

We convert SPSS proprietary formats (neural network, decision tree) into open standards that SageMaker can train and serve. Our engineers have deep experience with both platforms.

Can we keep vendor support during migration?+

Yes—your existing vendor support contract remains active as long as you keep it. You migrate at your own pace. If the renewal lapses, our third-party support covers most operational issues on SPSS while you finish the move. It is not vendor support and does not include vendor patches, but it gives you time without paying a full renewal.

What if our vendor contract lapses mid-migration?+

If your SPSS vendor contract expires partway through, our independent third-party support handles most operational issues—like break-fix and configuration help—on the legacy platform. This removes the pressure to pay a full renewal just to buy migration time. Note: this is not vendor support and does not include vendor patches.

Ready to start? Get a Free SPSS-to-SageMaker Workshop

Once your IBM SPSS Statistics workloads are running on Amazon SageMaker, let us help you optimize costs, monitor model drift, and manage your MLOps pipeline. Our managed services keep your environment lean and performant.

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