Data migration

Switch from your legacy system to NetSuite effortlessly

Tvarana data migration

Importance of data migration

Accounting platforms such as Quickbooks work well for smaller businesses, but rapid growth needs something more robust and reliable, like NetSuite. Data migration is an essential, but often challenging step in implementing a new accounting system. 

A major challenge faced by businesses while making the switch to NetSuite is the existence of data silos. Consolidating and cleaning up data to meet the requirements of NetSuite’s field and structure style before being imported is a step that is critical to the success of implementing a new system. Switching from your legacy system to NetSuite can feel daunting, but Tvarana can help ease the transition with a data migration process that is tried and true.

 

The Tvarana Advantage

Tvarana maintains an edge over other players in the data migration market based on four main parameters.

Tool

The built-in tool we have implemented at Tvarana for data migration is powerful in its functionalities. It works on the data to clean it, transform it from one format into another, and extend it with web services and external data. The tool works on a variety of file types such as TSV, CSV, Excel and JSON. It’s functionalities include- but are not limited to- detecting duplicate records, removing blank spaces, spell checks, referencing and mapping Entity fields.

Process

Tvarana has developed a robust process for migration, involving the following steps:

  • Defining Scorecard
  • Data Cleanup
  • Data Transformation
  • Data Loading
  • Data Reconciliation
  • Scorecard review

Reconciliation

You cannot trust your data without data verification. Tvarana’s rigorous reconciliation process leaves no stone unturned to ensure complete data fidelity, helping you rest easy. The reconciliation process covers:

  • Financial reports 
  • Customer and vendor open balances with AR/AP aging reports.

Delta Data Management

Delta data loading, or loading changes to preexisting data, needs to be handled with care during implementation. The Tvarana process works to identify potentially problematic scenarios and planning strategies around it.

  • Parallel run
  • Weekend cutoff
  • Month-end cutoff
  • Close in two systems
  • Retrospective data migration