As the speed of information growth exceeds in this new century, excessive data is making great troubles to human beings. However, there are so much potential and highly useful values hidden in the huge volume of data. Big Data has drawn huge attention from researchers in information sciences, policy and decision makers in governments and enterprises. Data analytic is the science of examining raw data with the purpose of drawing conclusions about that information. Data analytics is about discovering knowledge from large volumes data and applying it to the business. Machine learning is ideal for exploiting the opportunities hidden in big data. This chapter able to discover and display the patterns buried in the data using machine learning.
As the speed of information growth exceeds in this new century, excessive data is making great troubles to human beings. However, there are so much potential and highly useful values hidden in the huge volume of data. Big Data has drawn huge attention from researchers in information sciences, policy and decision makers in governments and enterprises. Data analytic is the science of examining raw data with the purpose of drawing conclusions about that information. Data analytics is about discovering knowledge from large volumes data and applying it to the business. Machine learning is ideal for exploiting the opportunities hidden in big data. This chapter able to discover and display the patterns buried in the data using machine learning.
E-commerce is selling and buying products in online shopping through the internet. When purchasing the products using internet, many security issues arise. These issues are to be addressed effectively and to be resolved. The security issue is an essential part of any transaction that takes place over the internet. Security becomes paramount not only for retailers but for any business that operates via the internet as the popularity of online shopping grows. This chapter focuses security protocols and their achievements in providing effective communication between end-users and business people.
The Internet of Things comprises billions of devices that can sense, communicate, compute and potentially actuate. The data generated by the Internet of Things are valuable and have the potential to drive innovative and novel applications which are one of the sources of Big Data. IoT connects real world objects to the internet using tiny sensors or embedded devices. One of the biggest advantages of the IoT is the increasing number of low-cost sensors available for many different kinds of functionalities. These sensors include a variety of devices and solutions. The trend is moving towards multi-sensor platforms that incorporate several sensing elements. In such environment, discovering, identifying, connecting and configuring sensor hardware are critical issues. The cloud-based IoT platforms can retrieve data from sensors. Therefore, IoT is a comprehensive inter-disciplinary technology, So, this chapter presents Better scheduling decisions should result in saving the time, utilization of resources and enable to meet the time constraints.
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