An empirical study on text analytics in big data

Today´s world is flooded with unstructured information. Big data is not just a description of raw volume but it has to real issue of usability. The major part of information retrieval is giant experience in big data. The real challenge is identifying or developing most cost effective and reliable methods for extracting value from all the terabytes and petabytes of data now available. That´s where big data analytics become necessary. Conventional analytics focused on structured data but these methods are not appropriate for large volume of unstructured data in order to extract knowledge. Text analytics is the way to extract significance from the unstructured text to find out patterns and transformations. The importance of text analytics is increased more in social media and business intelligence. This study reveals that big data text analytics can breed new insight to the world of text information and discusses various researches carried out in text analytics.