Projects on Big Data Hadoop

Projects on Big Data Hadoop

     Projects on Big Data Hadoop give a spunky research network for you to get praiseworthy achievements in your scientific life daily. Our team of professionals are initiated our Projects on Big Data Hadoop service with the full vim and vigorous of share our creativity and inventiveness for students and research academicians to do something new in their future. This is our major responsibility to take care of every student and research scholar’s projects on Big Data Hadoop. We have solicitude to give scientific creature by way of worldwide students and research scholars to this emerging world. Would you like to know about our standardized service? You can contact our world-taking experts.

Projects on Big Data Hadoop

    Projects on Big Data Hadoop offer pro-eminent way to carving your scientific profession sculpture. Our universal celebrated experts offer the amaze-balls training for students and research philosophers in all over the world. Because of the reason, we are experts in Hadoop tools and software including Spark, Pig, Mahout, Cassandra, apache Hadoop, R, MongoDB, Ambari, ArgoUML, Pentaho etc. We give limitless practical hours for you to become as a best Hadoop developer in this globe.

Related Research Areas on Big Data Hadoop:

  • Tools and software for massive big data processing
  • Privacy and security issues in Big data
  • Data mining techniques and tools in big data
  • Scalable architecture for massively parallel data processing
  • Scalable storage systems for big data
  • Social networks and large scale data analysis
  • Cloud computing platforms for big data analytics and adoption
  • Big data algorithms and models
  • Big data processing and parallel programming techniques
  • Big data analytics and management
  • Uncertain data management in big data
  • Anomaly detection in very large scale systems
  • Privacy preserving big data analytics
  • Machine learning methods to access big data
  • MapReduce architecture and Hadoop Programming
  • Business intelligence in big data analytics
  • Semantics and visualization over big data
  • Smart healthcare in big data analytics

Big data Hadoop Technologies and Tools:

  • Pig
  • Spark
  • Mahout
  • HBase 0.94.16
  • Pentaho
  • Apache Hadoop
  • Cassandra
  • MongoDB
  • R Programming
  • Ambari
  • J2SE
  • IntelliJ IDEA
  • Argo UML 0.34
  • Servlets
  • Java Database Connectivity
  • Eclipse –Indigo SR2

Our Other Service Categories for Students:

  • National/International Conference Support
  • PhD guidance and assistance
  • Journal paper writing service
  • Review articles and research articles writing
  • Research domain and topic selection assistance

Current Topics in Projects on Big Data Hadoop:

  • Scaling Cloud Resource Using Layered Multi-Dimensional Hidden Markov Approach for Big Data Streaming Applications
  • A Comprehensive Model for Federal Big Data Analytical Framework Validation and Management
  • Analysis of Big Data Powered Log for Computational Research Operations
  • Extreme Learning Machine for Big Data Using Parallel Multi Classification Algorithm
  • Evaluate Geo-Spatial Big Data Processing Performance in Parallel SECONDO Using Berlin-Mod and T-Drive
  • An Innovative Evolutionary Algorithm in Materialized View Selection for Speedup Big Data Query Processing
  • Apache Hadoop MapReduce for Implement Single Criteria Collaborative Filter in Big Data
  • CludSim and Cluster Based Load Balancing for Analyze Big Data in E-Commerce
  • Probabilistic Parallelization and Unsupervised Blocking for Distributed Big Data Record Matching
  • Classified Protection Model Used in Integrate Threat Intelligence and Big Data Analysis Technologies
  • Scalable and Structured Big Data Indexing and Discovery Based on MapReduce in Big Data Hadoop
  • Evaluate Extractive Text Summarization Technique Based on Unsupervised Learning for Large Scale Feedback and Review Data
  • Token Based Scheduler in Heterogeneous Big Data for Efficient GPU Utilization
  • Vital Big Data Sign for Severe Clinical Events Real Time Prediction and Discovery Using Learning Algorithms
  • Big Data Sensing Streams Using Efficient Security Mechanisms Based on Dynamic Prime Number