Emerging Trends and Challenges in Data Science and Big Data Analytics

In the recent decade, several technologies have boomed up due to recent development in many technologies. These technologies have changed the life of human being and are increasing the profit for individual, organisations like NetFlix, Alibaba, Flipkart, etc. Today in this world, maximum people are surrounded by smart objects or using smart objects to make their life easier to live and convenient. But, on another side life is being made easier to live by analytics companies/ industries. For example, which user like which type of plays, movies, songs, etc., things are extracted by many companies. Such recommendations are being made and being provided improved services to the respective users. Such jobs are being done by Data Scientist. Whereas, Data science (a future of Artificial Intelligence) is a multi-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured (labelled) and unstructured (unlabelled) data. Moreover this, Big Data Analytics are the analysis mechanism used in Data Science by Data Scientist. Several tools like Hadoop, etc., are used to analysis the large amount of data and used in predicting the valuable information/ making decisions. But, in analysing we faces several concerns like complexity, scalability, privacy leaking and trust. So, this article discusses about such concerns, challenges (rising) in this emerging field in detail (with a comparative analysis/ taxonomy).