Big Data PhD Thesis

Big Data PhD Thesis

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Big Data PhD Thesis

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Mostly, Big Data falling into the following reasons,

  • Privacy (Managing data with private trust)
  • Legislative (Use of data with respect to the permission)
  • Methodological (Data quality and Sustainability of Statistical methods)
  • Management (Directives and policies about the data and protection of data)
  • Technological (Issues related to Information Technology)
  • Financial (Data costs of sourcing data)

      …”Cloud computing is one of the emerging technologies in Big Data which allowed to storing huge amount of data including, structural, semi-structural and un-structural data”. There is some challenges and deployment needs to adapt these types of data.

What are the reasons to consider cloud computing?

  • Users can access data from anywhere
  • Hardware expensive is reduced and frequent hardware updates
  • High availability of the data
  • Keep organization with space and monitoring needs for data storage servers and devices
  • Multiple servers configured for multiple requests

Cloud Services for Big Data:

Amazon Web Services

-Compute and Networking

  • Route 53
  • VPC
  • Direct Connect
  • EC2

-Content and Storage Delivery

  • Amazon S3
  • Storage Gateway
  • Glacier
  • CloudFront

-Database

  • Elastic Cache
  • RDS
  • DynamoDB
  • Redshift

-Deployment and Management

  • Elastic Beanstalk
  • CloudFormation
  • CloudTrail
  • IAM
  • OpsWorks
  • CloudWatch

Future of Big Data in Cloud (Google Cloud Platform):

  • Data Warehouse Analytics (Google BigQuery)
  • Stream and Batch Data Processing (Google Cloud Data Flow)
  • Hadoop and Spark Management (Google Cloud Dataproc)
  • Powerful Data Exploration (Google Cloud Datalab)
  • Customized Data Support (Google Data Studio)
  • Intelligent Data Preparation (Google Cloud Dataprep)

Based on the above technology we write the following Big Data PhD Thesis,

  • An Improved Visualization Approach for Big Longitudinal Data to Help Behavioral Trajectory Pattern Recognition
  • Heterogeneous Urban Big Data Based Air Quality Estimation Using Extended Spatiotemporal Granger Causality Approach
  • Cyber Physical Framework for Integrative Genomic Association Microfluidics Driven Analysis
  • Formulation of Mathematical Programming in Smart Grid for Electricity Demand Optimal Load Shifting
  • Max-Min Fair Resource Allocation in Shared Clouds for Stream Big Data Analytics
  • Interactive Speed Query Engine on Temporary Data for Ad Hoc Queries
  • Different Machine Learning Approaches Comparison for Gestational Age Infants to Small Prediction
  • Security Situational Awareness Based on Big Data Analytic in Smart Grid Applications
  • Scalable Metadata Lookup Service in Data Centers for Distributed File Systems
  • Multi Task Learning and Deep Model Based Transfer for Analyze Biological Image
  • Social Media in Distinctive Metropolitan Areas to Understand Idiosyncratic Lifestyles
  • Clustering Affinity Propagation for Investment Risk Reduction and Intelligent Portfolio Diversification
  • Hybrid Database Converts for Air Pollution Monitoring Service Implementation
  • Smart Campus Using Big Data Technology on Energy Monitoring Service Construction
  • Free Energy Modeling and Frequency Domain Analysis for Differentiate true or False 4K Resolution