Data migration
, "nearly 40 percent of data migration projects were over time, over budget, or failed entirely." As such, to achieve an effective data migration, proper planning is critical. While the specifics of a data migration plan may vary—sometimes significantly—from project to project, the computing company IBM suggests there are three main phases to most any data migration project: planning, migration, and post-migration. Each of those phases has its own steps. During planning, dependencies and requirements are analyzed, migration scenarios get developed and tested, and a project plan that incorporates the prior information is created. During the migration phase, the plan is enacted, and during post-migration, the completeness and thoroughness of the migration is validated, documented, closed out, including any necessary decommissioning of legacy systems. For applications of moderate to high complexity, these data migration phases may be repeated several times before the new system is considered to be fully validated and deployed.
Data portability
Personal data are the basis for behavioral advertising, and early in the 21st century their value began to grow exponentially, at least as measured in the market capitalization of the major platforms holding personal data on their respective users. European Union regulators reacted to this perceived power imbalance between platforms and users, although much still hinges on the terms of consent given by users to the platforms. The concept of data portability comprises an attempt to correct the perceived power imbalance by introducing an element of competition allowing users to choose among platforms.
The right to data portability was laid down in the European Union's General Data Protection Regulation (GDPR) passed in April 2016. The regulation will apply to data processors, whether inside or outside the EU, if they process data on individuals who are physically located within an EU member state.