Big Data Analytics Projects for Students

Big Data Analytics Projects for Students

Big Data Analytics Projects for Students is a world class service offered by us with the goal of aiding young minds in their process of successfully completing their thesis bid data is an upcoming field.This also serves as a birthplace for many new kinds of data that are integrated with some existing traditional data. To do a perfect project based on big data, one must be through with all the emerging technology trends in the field. We have a team of intelligent experts, who are also ever at your service. Avail of our team’s service; together, we can combine our knowledge and creativity to deliver a perfect project on big data. Build Your Future with Our Foundation

Projects for Students

Big Data analytics projects for students started in order to get their ideas and creativity harnessed and we are always at your service to provide what you’re looking for big data is an advanced field which has more relevance to the world we live in. This makes it a promising field to do research work on; we possess enormous data regarding big data. We also have many experts in this field. So do make use of us, and together we can revolutionize the field of big data. Everything you need to know about big data: sometimes, usual basic software doesn’t have the capacity to handle large datasets. The 3vs in the technical field are Volume, Velocity, and also Variety, which make up big data.

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Important Characteristics of Big Data

  • Hadoop, spank, storm and also flink are some of the used frameworks.
  • Data sources, also big data frameworks are some secured big data
  • NuoDB, RDBMS, also NOSQL, MongoDB are the supported databases
  • Big data exploration and also merging of given data from various sources
  • Time and cost minimization is possible
  • Developed products, secured environment and also effective solutions.
  • Support for graphical user interface such as node box, flot and also ploymaps.
We offer Big Data Analytics Projects for Students based on the following,

Platform support

  • Solaris
  • Ubuntu linux
  • Mac Os X
  • Redhat enterprise Linux
  • Microsoft windows
  • SVSE linux
  • Elastic OS
  • Centos 6
  • And also Unix

File extension and Programming Language

  • R Programming (.r, .R, Rdata, .rds, also .rda)
  • Scala (.scala, sc-used for sparlk and also kafka)
  • Java (.java)
  • Python (.py, .pyc, .pyo, .pyd, .pyw, and also .pyz)

Development Tools and Software

Splice Machine (version 2.0):

                           -Makes use of standard SQL and also supports java script, Angular js, Python, java etc.

                           -Real time SQL on Hadoop database.

SAP in Memory:

                           -Tools also for application development are integrated with apache hadoop.

                           -Large workloads are also analyzed using this.

Talend (version 6.2.1):

                           -Big data open studio is served by means of open source software.

Pentaho (version

                           -Big data is visualized, analyzed and also blended.

                           -Platform which is embedded and also open with extensive analytics are offered.

Mark Logic (Mark Logic 8):

                           -Data filtering tools as well as geographical data is given

                           -Supports flexible API.

                           -Heavy data loads one dealt.

Massive Online Data Analytics Tools

  • Pentaho map reduce
  • HDFS file operation
  • Pentaho big data plug in
  • Amazon Web Services (Amazon EC2, S3)
  • NoSQL and NewSQL
  • Apache Spark
  • Also in Mahout Software Tool

These are the plugins that are used. It also provides real time big data stream mining support. In below, we have enumerated few algorithms for your reference.

  • Apriori algorithm.
  • KNN algorithm.
  • Naive Bayes algorithm.
  • Support vector machines.
  • Ada Boost algorithm.
  • Expectation maximization algorithm.
  • Page rank algorithm.
  • External memory and cache obliviousness.
  • Sketching and streaming.
  • Dimensionality reduction.
  • Fuzzy K-Means, and also Spectral Clustering
  • Canopy clustering and also in K-means clustering
  • Multilayer Perceptron algorithm
  • Hidden Markov Models

Major Research Areas in Big Data Analytics

  • Quantum measurements and metadata management.
  • Telecom and digital media solution.
  • Live drug response analysis system.
  • Universal access and easy retrievals.
  • Machine learning.
  • Sentiment analysis.
  • Fraud detection and offline productivity.
  • Data ordering response and de duplication.
  • Digital media and also in telecom applications.
  • Minimum learning curve and pattern detection.
  • Healthcare information exchange is secured and private.

The above-provided information is presented especially for you to get a clear idea about big data projects. If you still felt inadequate, you can contact us, and we will provide all the information regarding our big data analytic projects for students. Be part of the institute, and we promise you that you with pass out with flying colors.

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