Big Data (BD), with their potential to ascertain valued insights for enhanced decision-making
process, have recently attracted substantial interest from both academics and practitioners …

Storm has emerged as a promising computation platform for stream data processing. In this
paper, we first show inefficiencies of the current practice of Storm scheduling and challenges …

MapReduce has been widely recognized as an efficient tool for large-scale data analysis. It
achieves high performance by exploiting parallelism among processing nodes while …

Companies are increasingly moving their data processing to the cloud, for reasons of cost,
scalability, and convenience, among others. However, hosting multiple applications and …

Abstract Background: Big Data is a relatively new field of research and technology, and
literature reports a wide variety of concepts labeled with Big Data. The maturity of a research …

Most data analytics applications are industry/domain specific, eg, predicting patients at high
risk of being admitted to intensive care unit in the healthcare sector or predicting malicious …

Background: Big Data is a relatively new field of research and technology, and literature
reports a wide variety of concepts labeled with Big Data. The maturity of a research field can …

In this chapter, the business intelligence and social media analytics (SMA) are brought into
focus to address the strategies, methods, and technologies for managing the data analysis …

Many systems for big data processing have been developed to analyze and process huge
amount of data. One of them is Storm, whose target is stream data processing. The default …

Modern scientific collaborations require large-scale integration of various processes. Higher-
level dataflow languages are used on top of parallel and distributed dataflow systems to …