Hadoop Real Time Projects

      Hadoop Real Time Projects is the magnetic research medium to change your daydream into star of success.  We bring forward much of unique opportunity for our interns to gain more from us. Our predominance knowledgeable experts have a real time situation which grants more beneficiaries to twofold students and research academician’s knowledge. Our implementation training helps you to bridge the gap in knowledge procurement process. Scholars you can bring immense of programming experience which help you to gain excel and high confidence in real life settings. It helps you to stand phenomenally in your upcoming avocation. Our trained students and research scholars have firsthand experience to work in effective, challenging, collaborative on Hadoop paradigm. For more details, you can make contact with our Hadoop professionals without any delay.    Once you commit with us, you should be feeling on top of world……            

 Hadoop Real Time Projects           

     Hadoop Real Time Projects is an ultimate network for students and research fellows to give excellence of implementation training on Hadoop. Our project development training gives hands on high experience in the respective field of Hadoop. It reflects your work of verifiable reference and real time project experience on your professional resume which introduce candidate’s confidence in your knowledge. After our Hadoop training, you have an isolated personality and world identify you as a Hadoop expert.

Why we go for Hadoop?

-It scale-up thousands of nodes/computers

• Run queries against data
• Integrates data from multiple resources
• It handles unstructured data

-Fault-tolerance

• Self-healing
• File block replication

-MapReduce

• Good for processing large datasets
• Provide security features for complex jobs
• Distributed processing model

-Runs on Commodity Servers

• Affordable cost
• Easy to setup and use

We supported Hadoop on the following Things:

Supported Platforms:

• Windows/Linux –Cygwin
• Hadoop 1.2.1
• Java EE 8
• Java JDK 8

Hadoop Projects Development Tools:

• R-Programming
• Cassandra
• Apache Hadoop
• MongoDB
• Ambari
• HBase 0.94.16
• Apache Spark
• Apache Pig
• Apache Mahout
• Apache Pentaho
• J2SE
• IntelliJ IDEA
• ArgoUML 0.34
• Eclipse – Indigo SR2
• Java Database Connectivity
• Servlets
• Java Server Pages (JSP)

Hadoop Real-Time Project Ideas:

• Spatio-temporal and high dimensional data visual analytics
• Data Mining and Machine Learning for Visual Big data Analytics
• Information and Scientific Visualization
• Visual Representation and Interaction
• Cognition and Perception of Visual Information
• Sense making and analytical reasoning on Big Data
• Semantics-driven Visual Analytics
• Context-driven user querying
• Visual analytics evaluation methods
• High performance graphics for visualization
• Visual analytics foundations and algorithms
• Applications and advanced technologies for visual analytics
• Augmented and Virtual Reality for Visual Analytics
• Big Data Management and Transformation
• Visual analytics workflows and processes
• Visual analytics simulation

Other Related Areas:

• Complex event data processing
• Streaming as ETL
• Augmenting or Replacing SAS
• Data Consolidation
• Specialized Analysis
• HaaS (Hadoop as a Service)
• Streaming Analytics

    We are experts in Hadoop Real Time Projects, in below we emphasized few list of emerging topics in Hadoop framework,

• Real Time Big Data Processing by MapReduce Framework for Machine learning Using a Novel Scheme
• Fairness Consideration Based Effectual Dynamic Slot Allocation for MapReduce Clusters
• Parallel Inference Engine Based on MapReduce for RDF (Resource Description Framework) Reasoning
• MapReduce and Spark Programming for Cloud Data Mining Process
• Big Data and Internet of Things in Smart City Implementation
• Students Outcome Based Instructor’s Performance Discovery Using Big Data Analytics
• Big Data Insights Using Predictive Analytics and Business Intelligence in Big Data
• Online Load Balancing Scheme in Skewed Data Input MapReduce Using Mata-heuristics
• Enhance Performance of Network Traffic for Data Applications in MapReduce Using Online Algorithm in Dynamic Manner
• Ontology Based Semantics for Automated Predictive Big Data Analytics
• Neural Network Based Video Transcoding Using an Efficient Cloud Scheduling Scheme
• Unstructured Data with Big Data Paradigm for High Scalable Distributed Processing and Storage System
• Big Array Processing Based MapReduce Climate Data Using Spatiotemporal Indexing Scheme
• Anomaly Detection in Large Scale Distributed Heterogeneous Computing Framework for Data Streams
• Deterministic De-clustering Distribution in Data Intensive File Systems for Lightweight Autonomous Block Management