Big data is a big buzz phrase in the IT and business world right now – and there are a dizzying array of opinions on just what these two simple words really mean.
Some technology vendors in the legacy database or data warehouse spaces say “big data” simply refers to a traditional data warehousing scenario involving data volumes in either the single or multi-terabyte range. Such is not the case.
Today, big data isn’t limited to traditional data warehouse situations, but includes real-time or line-of-business data stores used as the primary data foundation for online applications that power key external or internal business systems.
It used to be that these transactional/real-time databases were typically “pruned” so they could be manageable from a data volume standpoint. Their most recent or “hot” data stayed in the database, and older information was archived to a data warehouse via extract-transform-load (ETL) routines.
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