ChainSys Data Migration for Salesforce (SFDC)


ChainSys Data Migration for Salesforce (SFDC)


Migrate master, reference, and transactional data from any source to Salesforce (SFDC)

Solution Description

ChainSys Smart Data Platform and proven methodology ensure data migration success, from any source CRM system(s) to Salesforce (SFDC), or vice versa, in as little as one-third the time. Trust ChainSys Smart Data Platform to deliver your next critical data migration project.

Use Cases, Key Features and Highlights

  • Migrate master, reference, and transaction data from any source CRM to Salesforce (SFDC), or vice versa.
  • 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 and load adaptors for Salesforce (SFDC) and other popular CRM systems, 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.