Migrate and convert your data with confidence


Change can come in several forms: a change of platform (e.g.: mainframe to client-server), business process changes, a need for additional application/process integration, mergers and acquisitions, regulatory compliance, new applications that deal differently with the same data, or simply to take advantage of the latest Information Management advances.

To best serve the organization, a data conversion/migration needs to take into account that business processes will continue to evolve, and that data and data quality will continue to fluctuate; a conversion solution must be ultimately adaptable while still enabling all critical applications to access and relay trustworthy and understandable data.


Source System Discovery & Profiling

  • Define the data types and values needed for the conversion and establish the size and complexity of the in-scope historical data.
  • Compare the data with the available documentation and compensate for any aberrations and inconsistencies.
  • Assess data quality, profiling, and cleansing rules and adapt them to applicable historical layers to ensure a consistent and accurate final data set.

Source to Target Mapping (STTM)

An essential component in developing the conversion code, the STTM provides solid footing for future evolution.

  • Experienced Business Analysts extract the business meaning of individual attributes and establish rules to ensure that the target system is accurately populated and forms a coherent whole.
  • We engage with subject matter experts to define and refine business and technical requirements, and transcribe the complex connections that make up any mature system in a way that will be meaningful to the ETL developers who will be tasked with the eventual conversion/migration.

Tool Selection

  • Make the right choice for your organization by leveraging Adastra’s vendor independence and deep knowledge of every major tool and technology in the Information Management space.
  • Use your existing tools and licenses more efficiently to mitigate costs and maximize your current investments
  • Employ (where appropriate) flexible arrangements for one-time or limited licensing needs.


  • Establish an effective risk-management process to ensure adequate fall-back capabilities, and an optimal approach for your organization and the profile of the data
  • Establish a strategy around which data subsets to convert first, and how to manage the changeover as seamlessly as possible.
  • As with all Adastra projects, work is subject to Adastra’s comprehensive SDLC methodology for Information Management projects (DW.360™), which will ensure your initiative is in line with established IM best practices.

Select Case Studies:

  • Credit Card Data Conversion (Financial Services)

  • Agile Data Conversion (Mining)