تجزیه و تحلیل داده های بزرگ برای افزایش تجربه مشتری با جمع آوری منابع A Review: Big Data Analytics for enhanced Customer Experiences with Crowd Sourcing

1. Introduction From past some years ,the biggest challenge companies are facing in this area with massive data is translation of business to models. Since it is just an evolving area, it is difficult even to define a problem thoroughly for example non technical staff can’t communicate the problem definition to the technical data scientists 1 . A large amount of data is produced from structured, semi structured and unstructured sources which makes it very difficult to manage information about customers usage. Mainly it’s the need of big Shopping giants like Amazon and Flipkart to process huge amount of data so as to process massive datasets to find hidden patterns. These data have to be extracted ,transformed and loaded to study patterns related to customer behavior and their interactions. Companies can improve the overall performance by using the customer feedbacks .Survey results from big data show them where they stand today in the competitive market. Crowd sourcing is an idea which is different from Big Data, crowdsourcing projects have shown the potential of using a wide group of real people to collect useful and accurate data 2 . To begin with, there cannot be reliable data management without some human involvement to check for errors and the administrators can easily make their own mistakes and put their own subjective slant on the filing of information 2 . Big data companies need crowdsourcing in their operations to ensure objectivity and diversity, prevent against errors more effectively and let social trends play a part in data examination. This combination of big data and crowdsourcing provides a way to modern data collection for customer experiences to make information more valuable, authentic and manageable. Big benefits can be reaped by pairing up crowdsourcing with big data.