Hadoop vs Spark

    In this article, we will see the key differences between Hadoop vs Spark. Before that, let us get a fix on what gave way to Hadoop and Spark. As all of us know, the growth of the Internet has resulted in huge volumes of data being continuously generated – what is called Big Data. This data in both structured and unstructured form is generated from primary sources such as social networks, the Internet of Things and traditional transactional business. Distributed Computing a new generation of Data Management of the Big Data is a revolutionary innovation in hardware and software technology. Distributed data processing facilitates the storage, processing, and access of this high velocity, large volume, and a wide variety of data.

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    Github Education Pack

    It is the most significant set of free tools and services brought to you by GitHub and its partners across the globe to the student at zero cost. From coding boot camps, logging service, code checkers, online IDEs, mass email service — everything is available to students at no cost. Yes, you heard that right. Any student who is 13 or above years of age and enrolled in a school or college (institution) can get this. Sounds awesome right? Read on!

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    Data Science vs Data Analytics

    The world today is incomplete without data. Humongous amounts of data are generated by users every day. If this data can be somehow analyzed and interpreted to capture what the user wants and make innovations accordingly, we could bring in a revolutionary system where businesses can provide state-of-the-art solutions to the problems faced by a common man and that too at low costs. Better still, this system can improvise and improve itself to be more innovative by the day. This revolution is data science and involves data analytics, machine learning and much more. 

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