Top Five Breakthrough technologies on Ph.D. in Big data/ Cloud Computing.
The exponential stage of this digital world has encouraged our lives to a huge extent, much better than a few decades ago when there were no technologies or improvisations. Now, a huge Big Data is generated. With the goal of data mining and organizing the data, the technologies have become a must among the Information Technology industries.
Ph.D. Enthusiasts and Data Analytics
The enthusiasts have the zeal of interest in Big Data and other related Big Data Analytics companies which are ruling to boost the list of future companies.
The craze among people to write a thesis has been a rapid rise due to the below-mentioned technologies:
- Apache Hadoop: It is basically a java-based open-source framework which comprises of the applications in storing, processing and mining of large datasets that are being collected. Hadoop works on the Hadoop distributed file system. This storage system splits the datasets in and stores them in a cluster of distributed nodes.
- Apache Hive: It is a data warehousing software that was built on this Hadoop structure. It is also used for data management, data summarization, data queries, and data analytics.
- Microsoft HDInsight: This is also a Hadoop based big data analytics which is available as a service in the cloud. It uses the Windows Azure Blob storage system that can support the Hadoop commands.
- NoSQL: This basically means a nonrelational database which has storage and data retrieval mechanism. It is used to handle unstructured data.
- MapReduce: It was termed as the core of Apache. It was used to process and generate large sets of data. It is handled using the ‘nap’ and reduces’ functions which are vigorously used in functional programming.
The other promoting technologies that can be used for the big data analytics Ph.D. projects are Polybase, Sqoop, Presto, BigData in Excel. This combination of tools and technologies are applied to the project as per the requirements of the project.
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