Comparative study of different Big Data Analytics Techniques for Unstructured Big Data

Big data is the current scenario requirement. Various social and business applications are producing large amount of data with great frequency. This large data processing is the most difficult task. Because extraction of the useful data will be some time cumbersome for the extraction of most suitable results. Because the results generated can enhance the future planning. Any type of suitability technique according the data nature is most difficult task. In current time for the processing of the data machine learning based tools are used. They works in two scenarios like supervised learning and other is unsupervised learning models. Supervised learning model based on building training set for the training purpose. So that machine can learn from the training and under stands the rules and regulations. So that while having testing set the learning can be applied on the big data to extract the useful aspect. Data either on health parameters of patient or on social networking related data machine learning based model is the most suitable technique. These techniques can further be enhanced to produce more efficient data.