Big Data Projects for Beginners

     Big Data Projects for Beginners give the prestigious awarding zone to gain fantastic diamond of achievements. Our splendid professionals have 15+ years of experience in guiding and support scholars from beginner to master by our updated and inventive knowledge. We are experts in the field of Big Data and give the best for scholars by our experience and expertise. Our professionals are given step by step training for beginners in every phase of implementation with the utmost mission of improve beginner knowledge in project development. We also provide immense of knowledge materials for our beginners to easily learn about Big Data without any complex. We are always available for you to solve your any kind of doubt or problem in big data.

Big Data Projects for Beginners

   Big Data Projects for Beginners provide the effectual knowledgeable environment for beginners with an admirable goal of create young experts in Big Data Paradigm. We give best implementation training with the knowledge in advanced technologies, mechanisms, approaches, algorithms, supported software and tools including MongoDB, MapReduce, Hadoop, Couchbase, EMR (Elastic MapReduce), Apache Spark and Apache Hive which is used for data integration in Big Data.     Here we briefly discuss about Big Data Projects for Beginners,

What is Big Data?

 “Big Data is a term for organizing large scale datasets that are so huge or complex to processing in conventional data processing software applications. Different challenges include storage, capture, analysis, processing, search, transfer, sharing, visualization, updating, querying and data privacy”.

What are the Big Data Problems?

• Virtualization (Virtual machine latency created timing issue)
• Automation Testing (Automated tools are not equipped)
• Large Dataset (Verify more data and automate the testing effort)
• Unavailability of Specific Tools (Single tool cannot perform end-to-end testing)
• Test Scripting (Scripting with high degree is required)
• Monitoring Solution (To monitor the real-time environment, limited solutions exist)
• Test Environment (Due to the large data size, special environment is required for testing)
• Diagnostic Solution (Analysis performance in bottleneck areas, tailored solution is highly required)
• Identify signal in the noise (Predict from huge lump of data)
• Data Silos (It occurs during Data Capturing)
• Data Inaccuracy (Due to the data silos ineffectiveness, data leads to inaccurate)
• Data Privacy (Data privacy leaking by un-legitimate users)
• Data Security (keep data safe as use data for a particular purpose)
• Data Discrimination (More difficult access the information)

Enable the following technologies to solve those issues:

• Production Reporting Tools
• Supply Chain Analytics
• Hadoop Software
• Data Integration
• Remove Duplicates
• New data verification
• Data Updating
• Integrate different systems of software and Hardware
• Machine Learning Approaches

Advantages of developing Big Data Projects:

• Mining, storing and analyzing of Big Data
• Market Prediction and Forecasting
• Implement new strategies/approaches for current trends
• Improves service dramatically
• Fraud detect in Fast
• Cost Savings technology
• Errors predicted immediately within the infrastructure

Big Data Applications Stages during Testing:

• MapReduce Validation
• Data Staging Validation
• Output Validation Phase
• Architecture testing
• Performance testing

         -Data processing

         -Data throughput

         -Sub-component performance

Tools/Languages we support for Beginners:

• SAS, R
• MySQL
• Excel, VBA
• C++, Java, Python
• Minitab, MATLAB, SPSS
• Gauss, GAMS, CPLEX
• Tableau, Spotfire
• Perl, PHP, Javascript
• Open source databases
• AWS and Cloud solutions

Applications of Big Data:

• Online Advertising
• Text Analytics
• Big Data Analytics
• Display Marketing
• Predictive Modeling
• Custom reporting
• Custom Insights
• Social Media Analytics
• Custom Dashboards
• Retail analytics
• Customer analytics
• Forecasting
• Revenue and pricing optimization

Here we listed few Big Data Projects for Beginners,

• Dynamic Neural Controller for Permanent magnet DC Motors Adaptive optimal Control
• Analytics and Ingestion Infrastructure Applied to Smart City Use Cases for Internet of Things
• Paradigm in Healthcare Application for Predict Mixed Type Multi-outcome
• Content Aware Partial Compression in Hadoop for Textual Big Data Analysis
• Analyze Big Real Time Visual Network Cameras Data Using Cloud Resource Management
• Scale Big HDT Semantic Data Compression Using an Innovative MapReduce Mechanism
• Automatic Distributed and Generated un Time Architecture for IoT (Internet of Things)
• Effective Missing Data Prediction Through Multivariable Time Series on Apache Spark
• Big Data Goal Orientation and Analytics for Business Process Reengineering in Modeling Framework
• Distribution Analysis for Airborne SAR Sea Clutter Data Using graphical Goodness of Fit
• MAC (Medium Access Control) Performance Analysis for Rayleigh Capture by Drive Thru Networks
• Detect Collaborative Spam by Confidentially Preserving Big Data Paradigm
• Energy Efficient Transmission Used in Digital Subscriber Lines by for Dynamic Resource Allocation
• Medical Image Analysis Using Deep Features Learning in Auto-encoder Neural Network
• Modeling Medical Texts for Skip Gram Approach Based Distributed Representation