The unfortunate truth is, big data has a lot of enemies -- and the largest group of opponents might just be those of us who have simply been force fed too much media spin on the subject in the first place. Big data clearly has a lot of negative factors (enemies) impacting how successfully we are able to deal with it in real world use cases. This list is intended as some kind of introduction to what may be a much more complex world of enemy factors in reality.
The unfortunate truth is, big data has a lot of enemies â and the largest group of opponents might just be those of us who have simply been force fed too much media spin on the subject in the first place. Of course there is no real big data i.e. all the data out there is still just data. As we know, big data is just another name for a large group of (often unstructured video, emails, sensor reports, logs etc.) data in the new massive âwebscaleâ world of the Internet.
Data is the plural (of datum) anyway, so why all the âbigâ data fuss in the first place?
The term big data has arisen to be defined something like: that amount of data that will not practically fit into a standard (relational) database for analysis and processing caused by the huge volumes of data created by the Internet of Things as well as machine-generated and transactional processes.
So if big data is so hard, who or what are the big data enemies that make dealing with it so tough?
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