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
Posts Tagged 'big data'
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
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
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
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
The Internet of Things (IoT) is rapidly emerging as a transformational paradigm with a multitude of products and services now available and being adopted by corporations as well as individuals seeking to harness the vast opportunities it offers. But we do face a major obstacle in realizing the full potential of the IoT. The sheer variety, volume and velocity of data generated by the IoT presents unprecedented challenges in deriving meaningful and actionable insights and calls for a strategic approach to data management and usage. These approaches also need to address business strategies, business processes, enterprise architecture, systems and applications, and security and privacy considerations. It is also important to examine and decide what data Read more
About two decades ago I thought I had a handle on big data. I was doing some data warehousing work with a telephone utility that had about 100 million transactions. That was a lot of data, I said to myself. Then, about 10 years ago, I was doing a review of a firm that audited financial trading on one of the major stock markets and I asked its big data guy how many transactions the company processed. His initial answer was, “On a slow day we get about 2.5 billion transactions.” “How many do you have on a busy day?” I asked with an air of shock. “4 or 5 billion,” he responded. Now that Read more