Data migration is the process of transferring data between storage types, formats or computer systems.
Data migration is usually performed programmatically to achieve an-automated migration, freeing up human resources from tedious tasks. According to a survey up to 84% of data migrations fail.
Migration addresses the possible obsolescence of the data carrier, but does not address the fact that certain technologies which run the data may be abandoned altogether, leaving migration useless.
It is time consuming as it must be repeated for every time a medium is reaches obsolescence- that is for all data objects stored on a certain media.
It is expensive as any institution must buy additional data storage media at each migration.
Common issues that people have encountered with data migration and can happen to you are:
Planning issues (everything squeezed into the last few weeks); Delaying the data migration effort until it adversely affects the system conversion effort/failing to make informed data migration decisions due to lack of cost and time estimates
Inability to access scarce internal subject matter experts
Failing to fully engage the business in the data migration project
Data glitches
Inadequate testing prior to actual data migration
Merging duplicate data - when more than one data source is being migrated into a new single database, very often there isn't a plan on identifying and resolving duplicates.
Lack of data profiling & analysis - (i.e. not realizing 10% of the 'integers' are actually 'characters'. Or mandatories with nulls, or spaces, etc.
Lack of reconciliation - queries are easy to get wrong. e.g someone said: a home and work address h1, w1 are migrated and suddenly there are two home addresses (h1,w1) and two work addresses (h1,w1). e.g. 10% of records got dropped due to a mis-matching key field. Even simple record counts can prevent these types of mistake.
Data migration is the process of transferring data between storage types, formats or computer systems.
Data migration is usually performed programmatically to achieve an-automated migration, freeing up human resources from tedious tasks. According to a survey up to 84% of data migrations fail.
For more- http://en.wikipedia.org/wiki/Data_migration
Some disadvantages of data migration are:
Migration addresses the possible obsolescence of the data carrier, but does not address the fact that certain technologies which run the data may be abandoned altogether, leaving migration useless.
It is time consuming as it must be repeated for every time a medium is reaches obsolescence- that is for all data objects stored on a certain media.
It is expensive as any institution must buy additional data storage media at each migration.
http://en.wikipedia.org/wiki/Data_migration#Disadvantages
Common issues that people have encountered with data migration and can happen to you are:
Planning issues (everything squeezed into the last few weeks); Delaying the data migration effort until it adversely affects the system conversion effort/failing to make informed data migration decisions due to lack of cost and time estimates
Inability to access scarce internal subject matter experts
Failing to fully engage the business in the data migration project
Data glitches
Inadequate testing prior to actual data migration
Merging duplicate data - when more than one data source is being migrated into a new single database, very often there isn't a plan on identifying and resolving duplicates.
Lack of data profiling & analysis - (i.e. not realizing 10% of the 'integers' are actually 'characters'. Or mandatories with nulls, or spaces, etc.
Lack of reconciliation - queries are easy to get wrong. e.g someone said: a home and work address h1, w1 are migrated and suddenly there are two home addresses (h1,w1) and two work addresses (h1,w1). e.g. 10% of records got dropped due to a mis-matching key field. Even simple record counts can prevent these types of mistake.
http://www.bcs.org/content/conBlogPost/73
http://www.tdan.com/view-articles/15145
http://www.bcs.org/content/conBlogPost/73