Major Advantages of Big Data Hadoop
With the kind of development that the big data Hadoop data analytical tool has been recipient of, by now everyone must be well aware of the field of Apache Hadoop. This is regardless of you belonging to an information technology background or not belonging to it. The whole idea of Apache Hadoop and the name in particular has been derived from a cute little elephant soft toy, which happened to be the favourite toy of a founder’s daughter. While the inspiration of the name may have come from a soft toy, this programming tool is anything but a soft toy.
Big Data Hadoop as it is popularly known around the data science world, is one such very important yet open sourced project, which offers the user with new ways of not just storing but also processing of huge amounts of data. The software framework of the same, is both written in Java for the purpose of distributed storage as well as distributed processing of enormous data sets on computer clusters that are built from commodity hardware. Hadoop happens to be a highly scalable storage platform, which basically means that it happens to work as an environment which can store and distribute large amounts of data sets across numerous data servers that will be operating in the most parallel fashion. Hadoop can run smoothly even when loads of data is involved as well as thousands of nodes are in place. It is one of the most cost effective storage solutions that a number of businesses have begun to opt for these days. Other traditional systems have as a rule proved to be extremely cost prohibitive, especially when it comes to scaling the same. The high costs in the past led to a lot of companies having to decrease the sample quality of their data and classify the same based on certain assumptions which would decide the value of the data.
With Hadoop in place, now business are enabled to easily access new data sources as well as to experiment by tapping into different types of data. This data could be both structured as well as unstructured. Thus this programming tool can be used by many businesses to derive extremely valuable data insights from the data sources such as social media, email conversations, as well as other kinds of clickstream data. Other various purposes that Hadoop can then be used for also include processing of logs, recommendation systems, data warehousing, and market campaign analysis as well. When it comes to this environment, the storage method is very uniquely devised on a system which literally goes ahead and ‘maps’ the data wherever it is located in clusters. The tools that are required for data processing also happen to be located on the same server where the enormous amounts of data is located, which makes it a cakewalk for the data analysts to work with the same. As this tool knows how to process terabytes of data in minutes and petabytes of data in hours, there is a great demand for Hadoop. There are a number of esteemed institutions like Imarticus Learning which help professionally train data aspirants in the use of Big Data Hadoop.