Summarized Notes for Large Scale Data Analysis

Large scale data is the major area of concern while processing textual data. To identify meaningful and actionable information from uncertain user-generated text, there exists the need to analyse large amount of data which is available in public domain. There are different kind of analysis which can be obtained from uncertain user-generated data.

Extracting information from online data, processing real time information, recording useful information at run time, classifying and analyzing related information from real time data stream are some of the major areas of concern, The graphical representation of information and map-reduce framework helps to keep track of important information out of huge bulk of data. Analysing social media data is the key trend these days which can be used to extract valuable information  from users' viewpoint.

Various applications for the large amount of data which can be used in research applications are marketing by big brands, using social network analysis for multiple applications like those of dynamics of marketing, dynamics of viral spread etc.. Further, topic modeling can be used to summarize and analyse the textual information. Industry is looking way for smarter business with data science based applications. Thus, data science has recently proved to be great source of income. There is huge amount of data which is available on internet regarding data science and big data. Many big data applications and new ideas have been discussed on internet.

For large scale data analysis, knowledge of statistics and machine learning is required.


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