The exponential surge in digitalization has influenced our lives to a great extent compared to a decade ago. It has generated a huge amount of Data. ‘Big Data’. With a mission of organizing and data mining, the below mentioned technologies have become the next buzzword amongst the Information Technology aficionados and PhD enthusiasts (Interesting!)
“The goal is to turn data into information, and information into insight.”
– Carly Fiorina
PhD Enthusiasts and Big Data analytics
PhD enthusiasts have a great deal of interest in Big Data and related analytics technologies as Big Data analytics companies are ruling the roost when we look the Forbes list of futuristic companies.
“Without big data analytics, companies are blind and deaf , wandering out onto the web like deer on a freeway.”
– Geoffrey Moore
This craze amongst people who work on a PhD thesis, as it’s the place world is going to be in tomorrow. This rapid rise in Thesis on big data analytics fuel the dissertations that are done using the breakthrough technologies mentioned below.
Apache Hadoop –It is a java based open source framework that has applications in distributed storage, processing and mining of huge datasets. Hadoop works based on Hadoop Distributed file System. This storage system splits the big data and distributes them across many nodes in a cluster.
Apache Hive –It is a data warehousing software that is built on Hadoop structure. It is primarily used for distributed data management, data summarization, generating queries and data analysis.
Microsoft HD Insight – it is a Hadoop based big data batch processing solution that is available as service in the cloud. It uses Windows Azure Blob storage as the file system that supports Hadoop file system commands.
NoSQL – Basically meaning non relational database that has the storage and data retrieval mechanism. This is primarily used to handle large amounts of unstructured data.
Mapreduce –It is usually termed as the core of Apache – Hadoop platform. It is a programming model that is used for processing and generating big data sets. It is inspired from the ‘map’ and ‘reduce’ functions that are widely used in functional programming.
Other Technologies
Other prominent big data and cloud computing technologies that are used for big data analytics PhD projects are Polybase, Sqoop, Presto, Big Data in Excel etc. The combinations of these tools and technologies are applied to the project as per the demands of the PhD project.
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