Analyzed the tweets regarding the top candidates in the 2016 election to predict the public sentiments towards each presidential candidate. The project attempts to solve the real world problem of understanding the sentiment towards election candidates based off the public live opinions and emotions rather than off of smaller, localized polls typically done by mainstream media corporations.
The aim of the project is to store terabytes of log information generated by the sensex website and extract meaning information out of it. The solution is based on the open source BigData s/w Hadoop .The data will be stored in Hadoop file system and processed using Map/Reduce jobs, Pig and export processed data to the MYSQL using SQOOP. By using struts will generate the graphs based on data in DB.
Designed a database which held information on restaurants, its features,chefs, customer details and customer reviews. Integrated with SSRS for providing visualization. Performed normalization, data generation, loading, clustering, indexing and partitioning.
Created a Java-based web application featured to have banking and Shopping in a single application developed using java, JSP and MySQL.
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