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Management
of data consistency is becoming more crucial as more functions are automated,
and as more decisions are made in “real-time” in which there is no leisure to
check the consistency of data.
No
single solution exists for ensuring data consistency; normally it is a
combination of technologies and best practices applied consistently across a
system. These technologies and best practices include:
· Clear
identification of primary sources of data
· Publish/subscribe,
so that systems, applications, and databases can “subscribe” to data, which
will be “published” to them whenever it changes
· Validation of
data consistency through a variety of data checks
· Alarming on
inconsistencies so that they can be corrected
· Automated
procedures for establishing or re-establishing consistent data after systems
are restarted or re-initialized
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