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Big Data technology has been in the industry limelight since five years. Also, it was expected that within these years big data would have impacted the transition scene i.e. from being speculated to practically ruling the roost. However, in 2017 Gartner analysts didn’t consider Big Data among the breakthrough technologies and Hype Cycle schedule. Instead, discussion on “the death of big data” was made.
Meanwhile, technologies and platforms for big data continue to evolve rapidly. Presently, large vendors like server and storage vendors, those software developers focusing on specific areas of big data; all interact actively with the Open Source community and release joint solutions. To make things easier and efficient to work with big data technologies, these vendors balance the product lines with missing features and optimize the existing ones. Interesting direction in this direction is the integration of data. For ex., it allows users to work with Hadoop data using tools like Structured Query Language (SQL), Business Intelligence (BI), etc.
Tools for Big Data are increasingly offered in local version when the product is installed into the customer’s data center and also in the cloud (public cloud). For ex., any customer can install hardware and software so as to work with big data and analyze it at home or rent it in the cloud.
However, the question arises as to how to transfer large amounts of data to the cloud? The easiest possible method is to accumulate and examine them directly into the cloud. Certain products are also available that helps in uploading data to the cloud and data integration. According to the rule, data is collected from various sources and then placed in the specified location that includes ‘cloud’.
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