The term ‘Big Data’ refers to the process of managing the huge arrival of big data volumes, requests, or tasks from the user device to the storage platforms like Hadoop. In other words, the type of information, rather than its amount, determines if it is classified as Big Data or otherwise.  Therefore, big data projects are gaining a lot of importance owing to their tremendous speed in data processing, huge quantity, and diversity which also enables cost-efficient and creative data processing technologies to derive valuable perceptions.

This article provides a deep insight into the fundamentals and advances of Big Data which is very much essential for your research.

Implementing Big Data Projects With Source Code for students

What is Big Data?

Big data is given the name because of its huge quantity of unstructured, semi-structured, and also structured data which can be mined while cannot be processed. The types of Big Data and their properties are given here for your reference, 

  • Unstructured data include audio and video files
  • Structured data includes SQL data store, schema-based data, and postgresql databases
  • Semi-structured data consists of Json arrays and objects, tweets, weblogs, txt, csv and xlsx files

The Big Data engineers, analysts, developers, and writers with us have gained world-class certification and thus we are capable of offering the best research support to all Big Data projects. The following are the important characteristics of Big Data that are offered at the eight V’s of it, 

  • Volume (quantity of the information that you are seeking to obtain)
  • Veracity (confidentiality and accuracy of the data being dealt with)
  • Variety (the nature of data)
  • Viscosity (the action being called for or been stuck)
  • Value (time-bound data availability)
  • Visualisation (understanding ability and supporting decision making)
  • Velocity (data gained and real-time opportunities to look for)
  • Virality (data being conveyed or presented)

You can get tremendous information for your Big Data research from us. The conventional methods of data processing and analysis are being replaced by Big Data techniques at a large scale to improve the business and working of an organization. At this juncture, it is highly appreciated that you take up Big Data projects for your research. You can enjoy a quality research experience with the help of our experts and

Taxonomy of Big Data management

It is significant for a researcher to look into different aspects of Big Data management including the problems and potential solutions in it or its taxonomy as detailed below

  • Storage of data
    • Clustering
      • Issues – high dimensional data storage, future data prediction difficulty, and delay in executing the process
      • Solutions – K means algorithm, Artificial bee colony, SQHAC, and optimization algorithms
    • Replication
      • Issues – inconsistency and lack of coordination and limitation in accessing speed
      • Solutions – Fuzzy Logic, dynamic data replication, optimization algorithm, artificial bee colony
    • Indexing
      • Issues – Updating index in variable data, Delay in data retrieval and reduced result accuracy
      • Solutions – Fuzzy Logic, support vector machine, composite tree
  • Data pre-processing
    • Data transmission
      • Issues – traffic management constraints transmission speed limitations and capacity-constrained link
      • Solutions – orthogonal Frequency division multiplexing, traffic separating, and wavelength division multiplexing
    • Data cleansing
      • Issues – Data duplication, missing and errors on inputs
      • Solutions – minimum covariance determinant, conditional functional dependencies and BIO – AJAX
  • Data processing
    • Data classification
      • Issues – constraints in processing large data sets, partitioning, and heterogeneity
      • Solutions – Statistics and Decision Trees
    • Prediction
      • Issues – Constraints in data quality accuracy in prediction and real-time data processing
      • Solutions – Neural Network and Support Vector Machine

To get detailed information regarding the availability, scalability, integrity, heterogeneity, and velocity and resource optimization factors of these potential Big Data solutions respective to the issues stated above you can reach out to us at any time. We offer technically high-quality research data for your Big Data projects. The references from top journals will surely fetch you a great perception of all aspects of Big Data research. Let us now have a look into the limitations in Big Data

Research Challenges in Big Data

The following are the three primary problems that Big Data presents:

  • Capacity
    • As Big Data is really large, storing such huge quantities of information is a huge challenge.
  • Data protection
    • Obviously, it must guarantee that every item of information is securely stored and that there is no data leakage or any compromises occur in some other manner.
  • Analysis and observations
    • When working with a large amount of data, it might be tough to draw information and insight, evaluate trends, and recognize similarities.

Our technical experts have guided a lot of Big Data projects and so we have got huge experience in handling these issues and challenges. Also, you can get any kind of query solved once you interact with our experts.  You can check out our website on Big Data for the potential solutions and remarkable breakthroughs that we recorded. What are the important Big Data techniques?

Big Data Techniques

The following are the common techniques used in Big Data analytics and all Big Data projects

  • Factor, survival, classification tree, and principal component analysis
  • Discrete choice, structural equation, hierarchical Bayes and time series models
  • Optimization, support vector machines, dimensionality reduction, and neural networks
  • Bayesian techniques and linear and nonlinear programming
  • Multicriteria decision-making methods 
  • Genetic algorithms and linear and non-linear regression

Usually, our experts provide you with all kinds of information required for handling these techniques. If you are looking for optimal procedure rules, protocols, steps, algorithms, and coding concerning any of these Big Data techniques then get in touch with our developers. We ensure to provide all necessary support in implementing codes and writing effective algorithms. In this regard let us have a look into the Big Data analytics algorithm below

Big Data analytics algorithms

  • Q learning, compressed sensing, and dimensionality reduction
  • Structured SVM, Relevance Vector Machines and temporal difference learning
  • Random Forest, Linde-Buzo-Gray and Winnow algorithms
  • Pulse coupled neural, radial basis function and Neural networks
  • Locality sensitive hashing, backpropagation and reinforcement learning
  • Numerical linear algebra, state action reward state action, and self organizing map
  • Sketching, streaming, external data, and catch obliviousness
  • ID3 extended 5 algorithm and Iterative Dichotomiser 3 or ID3 algorithm
  • Decision trees, association rule learning, and association rule mining
  • Eclat, meta Apriori and FP growth algorithms
  • Bootstrap aggregating, AdaBoost adaptive boosting, and Brown Boost boosting algorithm
  • Linear programming boosting (or LP boost) and logistic regression boosting (or LogitBoost)
  • ALOPEX which is the Machine learning algorithm based on correlation and K nearest neighbor algorithm
  • Zero attribute rule and one attribute rule algorithms
  • Hopfield Net for Recurrent neural network and Perceptron for feedforward neural networks

Our experts are highly familiar with all these algorithms since we have got more than two decades of experience in Big Data projects. With the huge source of reliable research data that we provide to you regarding these algorithms and along with the real-time implemented examples you can have a complete picture of the use of all these algorithms. What are the Big Data platforms?

Big Data Tools List

A researcher in Big Data needs to have a complete idea of all Big Data tools and platforms. We provide numerous big data project ideas for research scholars.So let us see the prominent platforms for different processes involved in Big Data analytics below

  • Platforms for Big Data processing
    • Big SQL Databases
      • Presto and HAWQ
      • IBM Big SQL and Impala
      • Hive and Spark SQL
    • Big stream Processing systems
      • S4 and Flink
      • Storm and infosphere streams
    • General purpose systems
      • Tez and Flink
      • Hadoop and spark
    • Big graph processing systems
      • Pregel and GraphX
      • GraphLab

Apart from these platforms, you need to have sound knowledge of the Big Data processing tools that you can use these platforms. 

  • Tools for Big Data processing
    • Compuware, AppDynamics, and VisualVM are the diagnostic tools
    • Ganglia, JMX utilities, Zabbix and Nagios are the monitoring tools
    • JMeter, Yahoo Cloud Serving Benchmark, and SandStorm are the performance test tools

For queries, regarding all the tools and platforms that we stated here, you can check out our website or connect with the technical team. We assure you that we provide you with full support in working with all these aspects. You can feel free to contact us at any time as we have got a customer support facility that functions day and night. Let us now look into the important applications of Big Data

Big Data Application Areas

  • Decoding human brain based on deep learning 
  • Collecting Big Data for a minimum period 
  • Integration of data from everywhere and data federation
  • Data access from all places in IoT analytics
  • Abstraction of data and data virtualization

In addition to these applications, we find huge potential to be applied in many other fields including specific areas of space science, medical and military, and so on. We are here to offer the most reliable, trusted, and authentic research support in any topics related to Big Data so that your project can contribute one of the best applications to the field. In this respect let us now talk about Big Data research areas

Research Areas for Big Data Projects

  • Web mining based on Big Data
    • Distributed Fuzzy Decision Trees based data access
    • Completely homomorphic encryption of cloud data
    • Heterogeneous MapReduce for adaptive task tuning
    • Real-time detection of spam drift and sentiment analysis in Twitter
  • Data mining based on Big Data 
    • Describing extract actions and predicting social emotions
    • Online social voting and machine learning-based disease diagnosis
  • Internet of things based on Big Data
    • Smart City based on virtual reality
    • Systems for Big Healthcare applications
    • Management of information in smart grids
    • Internet of Things and cloud integration in smart manufacturing systems
    • Management of business processes
  • Cloud Computing based on Big Data
    • Cloud-based digital entrepreneurship creation and processing data traffic
    • Hazard rate based assessment of reliability and BaaS services resource management
    • Evaluating data services quality and virtualized infrastructure protection

If you are searching for the best online research support on these project topics of Big Data research then you are at the right place. We are offering all kinds of research support like selecting a topic, designing the project by implementing codes and programming based on customization, checking for errors, upgrading the system, simulation, real-time implementation, recording the results, and so on. So you can reach out to us for any kind of technical assistance regarding Big Data projects. We now look into the recent trends in Big Data research

Top 5 Interesting Big Data Project Topics

Current Trends in Big Data

  • Scalability, effectiveness, structure, and mobility 
  • Trustworthiness modeling and methodologies 
  • Mining, networking, social media operations, and connectivity 
  • Acquiring data, integrating, potential solutions and cleaning 
  • Data pre-processing and mining based on semantics and social web searching
  • Big velocity data applications in cloud, grid, and stream data meaning
  • Graph mining, linking and multi-structured multimedia and big variety data

As we stated before we are one of the most trusted online research guidance providers in the world as we offer complete technical support to your Big Data projects. In this regard, it is quite important to mention that we are also providing other research-related supports like thesis writing,PhD research proposal in big data analytics, paper publication, assignment writing, proposal writing with a complete grammatical check, and an internal review. So you can get holistic research support from us. Let us now see other important research topics in Big Data

Top 7 Research Topics for Big Data Projects

  • Big Data analytics in quantum computing
  • Issues of privacy and security and graph databases
  • Efficient modeling of uncertainty, data transfer, and storage
  • Image, video, text, and other data processing based on real-time implementation of Big Data analytics
  • Parallel data processing in scalable architecture and scalability
  • Adopting and analysis using Big Data in cloud computing systems
  • Cost-effective complex cloud computation analysis

These research topics in Big Data have been given to you by analyzing the long-term issues and concerns that are being addressed by Big Data solutions and the recent trends in its research. You can get the benchmark references that can be used to carry out big data projects and in-depth Research once you contact us. 

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