ChainSys Data Migration for Peoplesoft


ChainSys Data Migration for Peoplesoft


Migrate master, reference, and transactional data from any source to Peoplesoft.

Solution Description

ChainSys Smart Data Platform and proven methodology ensure your data migration success from your current system to your new Peoplesoft system, in as little as one-third the time. Trust ChainSys Smart Data Platform to deliver your next critical data migration project.

Key Features and Highlights

  • Migrate master, reference, and transaction data from Peoplesoft to any target ERP.
  • Inline data profiling and improved data quality
  • Inline master data deduping, cleansing, enrichment
  • Inline data pre- and post-load validation
  • End-to-end data lineage and reconciliation
  • Parallel processing

Why ChainSys

  • Reduced Migration Project Risk and Timeline
  • Smooth Cutovers with Reduced Cutover Time
  • Satisfied Auditors

ChainSys Approach

ChainSys Smart Data Platform leverages pre-built object-level extract adaptors for Peoplesoft, as well as pre-built object-level load adaptors to Oracle E-Business Suite, Oracle Cloud ERP, SAP, Microsoft Dynamics 365, and others, to accelerate your extraction, mapping, transformation, and loading.

ChainSys Smart Data Platform rapidly extracts master, reference, and transactional data to assess and profile it, then configurable business rules are applied to match, merge, cleanse and enrich each data object as part of its data flow. Each data flow is then orchestrated to execute sequentially or in parallel, as required by the target system. Source data objects are loaded into the ChainSys data mart for pre-validation, transformation, corrections, before final loading into the target. End-to-end orchestrated data migrations (test cycles) are typically performed 3 to 5 times, prior to production cutover. With an increased number of test cycles and the first test cycle happening as early as one month into the data migration effort, the data quality improves significantly from one test cycle to the next. Full end-to-end data reconciliation of all data sources to all targets is performed with each iteration.