Nothing is quite so personal for programmers as what language they use. Why a data scientist, engineer, or application developer picks one over the other has as much to do with personal preference and their employers’ IT culture as it does the qualities and characteristics of the language itself. But when it comes to big data, there are some definite patterns that emerge.
The most important factor in choosing a programming language for a big data project is the goal at hand. If the organization is manipulating data, building analytics, and testing out machine learning models, they will probably choose a language that’s best suited for that task. If the organization is looking to operationalize a big data or Internet of Things (IoT) application, there are another set of languages that excel at that.
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