Data migration typically involves moving data from one platform to another. This process assumes a special significance in the payments industry due to the criticality and sensitivity of various key data elements that are generated and stored by various applications during the payment lifecycle. The sheer data volume generated during the payment lifecycle – from authorization, clearing and settlement, risk and fraud, disputes, loyalty, and billing – means that any migration of this data can potentially have a material impact on a company’s business.
One of the primary challenges faced by an organization that initiates a data migration project is to identify all the components that will be involved in the process and assess the accuracy and integrity of the data contained in them. Failure to do so generally leads to scope creep that will impact project timelines and cost. In addition, impact to dependent applications during the migration can cause significant business risk. To avoid these pitfalls, a seamless and proven migration methodology and framework must be deployed to insure a project is completed on time and on budget.
Based on its 25 years of experience in the payments industry and numerous data migration projects, RS Software has developed a framework designed to migrate data from legacy systems to open source solutions. The RS Software framework covers all phases of data migration projects including migration conceptualization, strategy identification, and customization of the solution, using business domain knowledge and tools for increasing efficiencies when moving data from the legacy source to the target open systems.
The RS Software approach protects organizations from the risk associated with the obsolescence of proprietary products by migrating their data to platforms that are flexible, scalable and open. This approach can lower the total cost of ownership of the data platform by up to 40 percent. The RS Software framework can be tailored to meet specific customer requirements with minimal reengineering of existing applications. This has allowed many of our customers to improve their time to market for data products by up to 20 percent.