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Did you know that Hadoop is a yellow toy elephant?
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Coming from an Economics and Finance background, algorithms, data structures, Big-O and even Big Data were all too foreign to me. The terms file system, throughput, containerisation, daemons, etc. had little to no meaning in my vocabulary.
Here is my attempt to explain Big Data to the man on the street (with some technical jargon thrown in for context).
What is Big Data?
Big Data literally means big data (in other words, a lot of data). The question should instead be, how big does data have to be to be considered Big Data? There is no fixed answer to this as it depends on the time at which one is asking it. As the amount of data continues to grow (exponentially), what is deemed as ‘Big’ today might not be considered ‘Big’ 10 years later. Today however, practitioners typically classify 1 terabyte (TB) of data or greater as ‘Big’ Data.
