PAUL JOHNSON
of Leading Edge explains the data temperature concept.
Blowing hot and cold
Paul Johnson: hot data is targeted at
the widest audience
It is often a dilemma for data warehouse managers to identify
and apply the right level of importance and relevance to data,
its location and the business users’ needs. An emerging approach,
which has yielded excellent results, is to view data as having
different ‘temperatures’.
Data temperature is a measure of the interaction and/or level
of interest and importance that surrounds that data. A data
warehouse containing sufficient data breadth (subject areas)
and depth (history) can always be considered to contain elements
of ‘hot’, ‘warm’ and ‘cold’ data.
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