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PhD Projects in Hadoop

Hadoop, referred as ‘backbone’ of big data analysis, provides a systematic framework to run jobs on multiple nodes of clusters. Hadoop provides world’s most reliable storage layer (HDFS), a batch processing engine (MapReduce) and a resource management layer (YARN).

This  Tool  Is  Widely Used  By Big Data Analysts Because It:

  • Has ability to store and process huge amounts of any kind of data, quickly.
  • Hadoop’s distributed computing model processes big data quickly.
  • Data and application processing are protected against hardware failure.
  • Unlike traditional relational databases, you don’t have to preprocess data before storing it.
  • The open-source framework is free and uses commodity hardware to store large quantities of data.
  • Little administration is required.

Due to its several advantages over other tools, scholars conducting projects in Hadoop is increasing drastically. But choosing a good project in Hadoop is not every scholar’s cup of tea. Fret no more! The consultants at Thesis India, are here to help you!

Some Of The PhD Projects in Hadoop Suggested By Our Consultants Are:

  • Hadoop Mapreduce based data prediction approach for classifying bankrupted data
  • Optimization based performance enhancement in Hadoop-Based Hybrid Cloud using Data Prefetching and File Synchronization.
  • Big data analytics for health informatics based on energy-efficient hadoop functionality.
  • Prediction of diseases from big data in hadoop environment using data mining based machine learning approach.

To obtain such cutting-edge projects, write to us at helpforphd@thesisindia.in. Kindly mention your specific requirements and area of interest so that we can craft the project according. You can also get in touch with us if you have already finalised a specific issue you will be working on and need assistance to choose a topic within that issue.

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Add Research Proposal/Synopsis where we shall provide you with the proposal with research objectives, proposed methodology and expected outcomes.
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