Research Topics in Big Data Analytics

Research Topics in Big Data Analytics

    Research Topics in Big Data Analytics offers you an innovative platform to update your knowledge in research. Our current trends updated technical team has full of certified engineers and experienced professionals to provide precise guidance for research scholars and students. We serve for students and research scholars through our 120+ branches in worldwide. Many numbers of research scholars and students can come from various countries to do their research with us. Our institute has certified by ISO 9001.2000 for the best quality of project and research guidance. We motivate and equip the student’s research in their appropriate area through our Research Topics in Big Data service. Initially, we discuss with the 1000+ research topics with you, if you committed with us we provide full support at the end of your research completion. Over the 10+ decades we are working in this field and capable to handle any complex problem with help of our experienced professionals.

Research Topics in Big Data Analytics

  Research Topics in Big Data Analytics brings you an innovative idea to shine your research career successfully. We support for research scholars and students in the following types of big data like structured data (CRM, ERP, Enterprise), unstructured data (Social media, videos, documents and machine sensor) and semi structured data (EDN, Transactions, XML/SON). We use two major technologies for big data processing like operational big data (MongoDB, NoSQL) and analytical big data (MapReduce, Massively parallel processing). We ensure that the quality of work and precise research guidance within a stipulated time. We provide support for all kinds of the students from BE, BTech, ME, MTech, MPhil, MCA to PhD, MS. Now let’s have a glance of big data analysis for your reference,

Major Research in Big Data Analytics:

  • Hive
  • Tableau
  • AWS Phyton
  • GraphX
  • R,
  • Hadoop,
  • Micro soft azure
  • Cloudera
  • MapR converged data platform
  • WSO2 big data analyst platform

  The following areas we have talk about major big data processing open source tool Hadoop for your convenience,

Big Data Open Source Tool – Hadoop

Hadoop and its features:

 —“Hadoop is an open source software framework which is used to processing in parallel fashion using Map reduce algorithm (Store and process large amount of data efficiently)”

  • Processing power and massive storage
  • Open source software that is free
  • Hadoop framework allowed running and developing software applications

Key Supports and Features:

  • I/O handling and efficient memory
  • Support Jar files and self-contained library
  • Reduce model and scalable map supports
  • Map reduce API and data co-location supports
  • Communication using REST based interface which minimizes the number of ports opened in the network
  • Major benefits like fault tolerant, cost effective, scalable and high computing power
  • NoSQL databases, MongoDB, Cassandra, Hive and HBase for database access
  • Data quality, standardization and data security for major issues using Hadoop lacking tools
  • Apache storm, Apache shark, Cascading, Apache Hive and Apache Pig supports
  • C++, PHP,C#, Erlang, Perl, Ruby, Java, Python and Haskell languages are used to programming
  • Windows, Unix, Mac OS X are supporting platform with GUI using HUE

Core Modules of Hadoop:

  • Provides libraries and utilities [Hadoop Common]
  • Java based system to store data across multiple machines [Hadoop Distributed File System]
  • Parallel processing large data [MapReduce]
  • Used to schedule and handle resource requests [YARN- Yet Another Resource Negotiator]

Major Algorithms Used:

  • Mean shift clustering
  • Parallel frequent pattern mining
  • K-Means clustering algorithm
  • Fuzzy K-Means Clustering
  • Latent dirichlet allocation
  • Parallel frequent pattern mining
  • Page rank algorithm
  • Linear regression
  • Random forest
  • Apriori algorithm
  • Artificial neural networks
  • Complementary Naïve Bayes Classifier
  • Random forest decision tree based classifier

Major Applications and Research Areas in Hadoop:

Supported Applications:

  • Hadoop for big data analytics
  • Web recommendation system
  • Low cost hardware’s for store social media, sensor, machine, scientific and transactional data
  • Enterprise data warehouse for advanced analytics, query and reporting
  • To process ETL and data quality tasks in parallel using commercial data management technology [Act as data lake]
  • Big data in healthcare industry
  • Cancer treatments and genomics using Hadoop technology
  • Monitoring patient vitals Hadoop technological
  • Health care intelligent
  • Fraud prevention and detection

Supported Research Areas:

  • Hadoop security design issues
  • Long running services using HOD provisioning
  • Campus work queuing systems using HOD ports
  • HDFS Namespace expansion
  • MR framework for shuffle and sort optimization
  • Integration of Hadoop tools with virtualization
  • Performance enhancement of Map reduce framework
  • Hadoop compatible framework for identification network topology and diagnosing hardware
  • Block placement in HDFS and modeling of replication policies


  The above information provided by us to make you very comfortable with our Research Topics in Big Data Analytics. We provide additional support for Thesis writing, Journal paper writing, Project development and Journal publication etc. If you’ve got a specific question about our services, then why not check out our website and get in touch with us. Our online service is available at 24×7.

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  We will make your research work successful to create research path good enough……..