TOREADOR Labs offer a Big Data Analytics-as-a-Service environment for testing simplified but real-life Big Data analytics vertical scenarios. Users are challenged with requirements, described from a business perspective, and are requested to compare alternative options, investigating the consequences of their choices. This “trial and error” approach brings up the interconnections and interferen...

There has been much hype about big data analytics – a collection of technologies, including the Hadoop distributed file system, NoSQL databases, and machine learning tools. One study estimated that it can generate hundreds of billions of dollars of value across industries [1]. Another study reported that 75 of telecom operators surveyed would implement big data initiatives by 2017 [2]. Every o...

The current paper highlights the advantages of big data analytics and business intelligence in the healthcare industry. In the paper are reviewed the Real-Time Healthcare Analytics Solutions for Preventative Medicine provided by SAP and the different ideas realized by possible customers for new applications in Healthcare industry in order to demonstrate that the healthcare system can and should...

Fueled by the Internet of things (IoT) and big data, business analytics is an essential capability for digital transformation.3 However, some long-established companies have experienced challenges in attempting to adopt new digital technologies, including business analytics, and derive value from them.4 Some organizational requirements for successfully using data-driven insights—such as horizon...

-------------------------------------------------------------------ABSTRACT------------------------------------------------------------Rapid technological advancements in recent technologies have led to inundation of data from diverse domains like scientific generated data, web, business intelligence and medical science over the past few years. The concept of big data was put to capture the mea...

The enormous amount of big data datasets impose the needs for effective data filtering technique to accelerate the analytics process. We propose a Versatile Searchable File System, VSFS, which provides a transparent, flexible and near real-time file-level data filtering service by searching files directly through the file system. Therefore, big data analytics applications can transparently util...

In the era of accelerating digitization and advanced big data analytics, harnessing quality data for designing and delivering state-of-the-art services will enable innovative business models and management approaches (Boyd and Crawford, 2012; Brynjolfsson and McAfee, 2014) and yield an array of consequences. Among other consequences, digitization and big data analytics reshape business models a...

The amount of data stored by banks is rapidly increasing and provides the opportunity for banks to conduct predictive analytics and enhance its businesses. However, data scientists are facing large challenges, handling the massive amount of data efficiently and generating insights with real business value. In this paper, the Intelligent Customer Analytics for Recognition and Exploration (iCARE)...

Predictive analytics in the big data era is taking on an ever increasingly important role. Issues related to choice on modeling technique, estimation procedure (or algorithm) and efficient execution can present significant challenges. For example, selection of appropriate and optimal models for big data analytics often requires careful investigation and considerable expertise which might not al...

Smart manufacturing (SM) is a term generally applied to the improvement in manufacturing operations through integration of systems, linking of physical and cyber capabilities, and taking advantage of information including leveraging the big data evolution. SM adoption has been occurring unevenly across industries, thus there is an opportunity to look to other industries to determine solution an...