Editing Data migration (section)

==The standard phases==
{{As of|2011}}, "nearly 40 percent of data migration projects were over time, over budget, or failed entirely."<ref name="MorrisPractical12"/><ref name="HowardData11">{{cite web |url=https://www.bloorresearch.com/research/data-migration-report-2011/ |title=Data Migration Report - 2011 |author=Howard, P. |publisher=Bloor Research International Limited |date=23 August 2011 |access-date=20 July 2018}}</ref> Thus, proper planning is critical for an effective data migration. While the specifics of a data migration plan may vary—sometimes significantly—from project to project, [[IBM]] suggests there are three main phases to most any data migration project: planning, migration, and post-migration.<ref name="DufrasneDS8870_17" /> 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, and closed out, including any necessary decommissioning of legacy systems.<ref name="DufrasneDS8870_17" /> 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.

'''Planning''': The data and applications to be migrated are selected based on business, project, and technical requirements and dependencies. Hardware and bandwidth requirements are analyzed. Feasible migration and back-out scenarios are developed, as well as the associated tests, automation scripts, [[Data mapping|mappings]], and procedures. Data cleansing and transformation requirements are also gauged for [[File format|data formats]] to improve [[data quality]] and to eliminate [[data duplication|redundant]] or obsolete information. Migration architecture is decided on and developed, any necessary software licenses are obtained, and change management processes are started.<ref name="MorrisPractical12"/><ref name="DufrasneDS8870_17" />

'''Migration''': Hardware and software requirements are validated, and migration procedures are customized as needed. Some sort of pre-validation testing may also occur to ensure requirements and customized settings function as expected. If all is deemed well, migration begins, including the primary acts of [[data extraction]], where data is read from the old system, and [[data loading]], where data is written to the new system. Additional verification steps ensure the developed migration plan was enacted in full.<ref name="MorrisPractical12"/><ref name="DufrasneDS8870_17" />

'''Post-migration''': After data migration, results are subjected to [[data verification]] to determine whether data was accurately translated, is complete, and supports processes in the new system. During verification, there may be a need for a parallel run of both systems to identify areas of disparity and forestall erroneous [[data loss]]. Additional documentation and reporting of the migration project is conducted, and once the migration is validated complete, legacy systems may also be decommissioned. Migration close-out meetings will officially end the migration process.<ref name="MorrisPractical12"/><ref name="DufrasneDS8870_17" />

===Project versus process===
There is a difference between data migration and [[data integration]] activities. Data migration is a project through which data will be moved or copied from one environment to another, and removed or decommissioned in the source. During the migration (which can take place over months or even years), data can flow in multiple directions, and there may be multiple simultaneous migrations. The ETL ([[extract, transform, load]]) actions will be necessary, although the means of achieving these may not be those traditionally associated with the ETL acronym.

Data integration, by contrast, is a permanent part of the [[Information technology architecture|IT architecture]], and is responsible for the way data flows between the various applications and data stores—and is a process rather than a project activity. Standard ETL technologies designed to supply data from operational systems to data warehouses would fit within the latter category.<ref name="KingData16">{{cite web |url=https://solutionsreview.com/data-integration/data-integration-vs-data-migration-whats-the-difference/ |title=Data Integration vs. Data Migration; What's the Difference? |author=King, T. |work=Solutions Review - Data Integration |publisher=LeadSpark, Inc |date=17 August 2016 |access-date=20 July 2018}}</ref>