Big data analytics is the process of examining large data sets to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful business information. The analytical findings can lead to more effective marketing, new revenue opportunities, better customer service, improved operational efficiency, competitive advantages over rival organizations and other business benefits.
The primary goal of big data analytics is to help companies make more informed business decisions by enabling data scientists, predictive modelers and other analytics professionals to analyze large volumes of transaction data, as well as other forms of data that may be untapped by conventional business intelligence programs. That could include Web server logs and Internet clickstream data, social media content and social network activity reports, text from customer emails and survey responses, mobile-phone call detail records and machine data captured by sensors connected to the Internet of Things.
The most highly used database NoSQL used in Big Data and real-time web applications technologies, frequently correlated with unstructured data in last year’s version of trends in Big Data. NoSQL database as a leading piece of the enterprise in IT environment becomes clear as the benefits of schema-less database concepts become more pronounced.
Value dimension talks of identification of value added information. Higher the consolidation, cleansing, consistency of information,
there are increased chances of precise decision making.
