Posts Tagged 'big data'

Nov 292017
 
Using Big Data Analytics to Support Higher Ed Students

Cutter Consortium Fellow Vince Kellen continues to blaze the trail by using big data to improve the Higher Ed experience — not just for students, but also for educators, advisers, and administrators. In addition to being a Cutter Consortium Fellow, Vince is the CIO at University of California, San Diego (UCSD), where he is leading the university’s roll out of the Student Activity Hub, which gives real-time insight into student behavior and performance. UCSD can analyze and correlate the data and use it to create more positive outcomes — in this case, improved retention and graduation rates. Plus, as Edscoop recently reported in its profile of Kellen and the UCSD Activity Hub project, the actionable data can Read more

Sep 012017
 
[Call for Papers] Big Data Trends: Predictive Analytics, Machine Learning, and Cloud

With data being collected by organizations at a staggering rate, the demand for analytics to leverage the insight from this data is growing just as fast. Big data can viewed as a gateway to new opportunities, as a means of managing risks, or as a tool to improve business sustainability. Oftentimes, big data is associated with two keywords: analytics and technologies. These keywords represent an evolving suite of trends – from descriptive, predictive and prescriptive analytics to the application of Machine Learning, and Cloud technologies. Continuously monitoring these trends in analytical approaches and technological breakthroughs in the context of Big Data and applying them to produce business value is the key to survival in this Read more

Apr 282017
 
Call for Papers: Digital Transformation in the Industrial Sector

Early adopters of interconnected digital technologies in the industrial sector are realizing the benefits of improvements in operational efficiencies, productivity, safety, cost savings, profitability, and customer engagement and satisfaction. These technologies include those related to the IIoT movement such as AI, machine learning, big data, predictive analytics, machine-to-machine communication, and blockchain. Industries in the manufacturing, energy, utilities, automotive, and aviation sectors, to name a few, are capitalizing on investments in these revolutionary technologies. An upcoming issue of Cutter Business Technology Journal with Guest Editors Patrikakis Charalampos and Jose Barbosa will examine emerging trends and strategies in digital transformation in the industrial sector. How are IIoT, predictive analytics, AI, big data, blockchain, and other technologies being Read more

Apr 172017
 
Data-centric Protection and Security: What are the Trends?

Data-centric protection and security focuses on the organization’s sensitive data (as opposed to its overall computer networks and applications). This is accomplished by locating, identifying, and cataloging sensitive data as well as by applying encryption, data masking, and policy-based data access controls (and end-user monitoring) to protect data residing across multiple enterprise environments. To what extent are organizations adopting, or planning to adopt, data-centric protection and security practices? In a recent Cutter Consortium survey, Senior Consultant Curt Hall asked 50 organizations about their data protection practices to shed some light on this important question. As shown in the figure below, more than a third (37%) of surveyed organizations currently have data-centric protection and security practices in place.   Read more

Jun 142016
 

The boundary between machine capabilities and what once seemed uniquely human has certainly moved over the years, justifying concerns that the relatively new field of roboethics addresses. Roboethics goes beyond job losses and looks at the impact of robotization on society as a whole; that is the major topic here. (I will address job losses at the end.) An algorithm can be unethical in both obvious and subtle ways. It could be illegal, as may have been the case with Volkswagen’s engine management algorithms for its “clean” diesel engines. It could be unethical in the sense that it violates a sense of fair play. More subtly, an algorithm could take on decision-­making roles that a Read more

May 032016
 
Five Perspectives on Cognitive Computing

Cognitive computing is among the major trends in computing today and seems destined to change how business people think about the ways in which computers can be used in business environments. “Cognitive computing” is a vague term used in a myriad of ways. Given the confusion in the market as to the nature of cognitive computing, our recent Executive Report (Part I in a two-part series) describes what we mean by cognitive computing by exploring five different perspectives on the topic: (1) rules-based expert systems, (2) big data and data mining, (3) neural networks, (4) IBM’s Watson, and (5) Google’s AlphaGo. Here is a brief description of each. Rules-Based Expert Systems There have been other attempts to commercialize artificial intelligence Read more

Mar 282016
 
Call for Papers: Big Data Analytics Success Hinges on the Four "Ps" — Preparation, People, Prediction, Production

Analytics — deep, predictive, operational, (insert preferred flavor here) — has climbed to the top of business executives wish lists in the past few years. The explosion of big data from social media sources and the coming supernova from the Internet of Things promises complete understanding of customer needs as well as the prediction/influencing of future behavior. With sufficient data, best of breed algorithms, faster computers, and emerging deep learning approaches — statistical correlation will become a largely exact science. Understanding causation will become an unnecessary luxury. Welcome to the analytics nirvana. Of course, inspiration and implementation often diverge. The day-to-day practicality of big data analytics continues to raise ongoing challenges. The “P-words” — preparation, people, prediction, and production point Read more