ABSTRACT
Technology and business conditions are ripe for Big Data projects. The nature of Big Data is data whose scale, diversity, and complexity require new architecture, techniques, and algorithms to manage and extract hidden knowledge from it. The majority of Big Data projects fall into one of two broad categories: storage driven and application driven. The statistical data shows that as the size of implementations grow, data-driven companies constantly seek to improve the ratio of users per administrator, thereby reducing the incremental cost of growth and increasing user self-sufficiency. The new computer, network, and storage capabilities, Mahout tool to facilitate machine learning, and real-time data exploration discovery and predictive analysis have provided deeper insights into business operations data in the form of fast, wide, and deep dashboards. In essence, raw Big Data is the sum of structured, semi-structured, and un-structured data. Data is information converted into binary digital form.
