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, this Executive Summary and its accompanying Executive Report describe 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.

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, this Executive Summary and its accompanying Executive Report describe 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.

Cognitive computing will revolutionize how organizations use computers. In this Executive Report, we consider the nature of cognitive computing. We look at the topic from five different perspectives, including: (1) rules-based expert systems, (2) big data and data mining, (3) neural networks, (4) IBM’s Watson, and (5) Google’s AlphaGo. We conclude that cognitive computing isn’t a specific new technology, but rather a variety of different technologies and complex architectures used to solve complicated and challenging problems.

Cognitive computing will revolutionize how organizations use computers. In this Executive Report, we consider the nature of cognitive computing. We look at the topic from five different perspectives, including: (1) rules-based expert systems, (2) big data and data mining, (3) neural networks, (4) IBM’s Watson, and (5) Google’s AlphaGo. We conclude that cognitive computing isn’t a specific new technology, but rather a variety of different technologies and complex architectures used to solve complicated and challenging problems.

It may be fair to say that many of the problems people see with enterprise architecture come from the name that the profession has given itself. “Architecture” implies a responsibility for the overall structure of the organization, a role that involves controlling and approving any changes to how the parts are put together. By analogy, this places the enterprise architect in a role similar to that of a building architect, with an overall responsibility for the structure of the enterprise.

Many have felt that “urban planner” is a better meta­phor, because the urban planner looks at how all the individual buildings fit together, considers how the structure and layout of a city affect the lives of its inhabitants, and helps to realize the overall vision of the city. I agree that this metaphor is better, and I think the evolution of urban planning provides some additional insights.

Emotion recognition platforms are now available that use neural networks and other machine learning algorithms to analyze and measure the facial expressions of subjects appearing in photos and video in order to determine their emotional state. Such analysis may take place on large collections of photo and video files residing in databases. It can also be performed in near real-time on images captured live — for example, for security scenarios or in-store retail applications involving shopper response measurement.

Software has been a crucible of management practice. Developing software requires a wide mix of types of work from mostly routine to highly innovative. For that reason, there is no one-size-fits-all solution to software development. While Agile does not fully solve the development management problem and is still evolving, there are important lessons we can learn from Agile principles for a wide range of business practices.

A digital transformation isn't just launching a brand on social media, hosting an electronic storefront, or connecting the enterprise workforce. Nor is it activating big data or analytics to synthesize new differentiators. A digital transformation requires escape from the routine mindset of business strategy to discover adjacent opportunities and strategies that create an asymmetric competitive advantage (i.e., a powerful advantage that denies competitors the use of similar strategies and tactics).

There has been a long-standing debate on what is the right ratio of developers to QA (dev-QA) on software engineering teams. Many managers face this debate on a regular basis. Some people argue that you need to keep a 1-to-1 ratio of dev-QA, whereas others say that you need no QA people on The Team and that developers should be responsible for the code they write.

Although certainly not a complete replacement for the highly customized applications that have characterized most enterprise IoT implementations to date, domain-specific IoT and industry-specific solutions offer end-user organizations a (relatively) less painful way of putting their IoT plans and initiatives into production.

In this issue of The Cutter Edge: Preparing for IoT Disruption | Six Ways to Reduce Tech Debt | New Cutter IT Journal

Part II of this series described the conceptual, IDEAL architecture required for a modern, all-inclusive information management environment. I proposed that such an architecture provides the blueprint for a data lake, which should be considered from the point of view of the three “thinking spaces”: information, process, and people. The architectural principles are encapsulated in the acronymic name: integrated, distributed, emergent, adaptive, and latent. Latent, or hidden, implies that these three thinking spaces are not a representation of how this architecture will be built. That it is the role of a logical architecture.

Clearly, one of the top business drivers behind crowdsourcing is that it can be relatively cheaper than outsourcing. An equally important business driver is that it enables businesses to promote creativity and excel at innovation while leveraging resources and collaborating inside and outside their own organizational boundaries. The creativity component arises from the fact that the ideation of a concept desired or solicited by the business or enterprise requires vision and resourcefulness. It involves the imaginative mindset of a varied and often intuitive, skilled group of professionals as well as a broad range of users (specifically, untapped expert customers). The innovation element is also significant. Creativity, creative thinking, and intuition have a common connection to innovation. Creative thinking offers an avenue for intuition to generate pragmatic ideas, and ideas transform into innovation. More important, crowdsourcing establishes a new channel for communication and collaboration among external users and experts and an enter­prise’s employees, partners, and associates. This collaborative effort ultimately instills the spirit of innovation in the enterprise. This Executive Update explores how to best leverage crowdsourcing in your enterprise, using a case study in digital healthcare.

This course focuses on extending the basic business architecture through strategy, product, initiative and stakeholder mapping. You'll learn how to leverage business architecture to benefit related disciplines including business modeling, Lean Six Sigma, business process management and case management.

In this all-new webinar, Cutter Senior Consultant Whynde Kuehn provides a practical approach for establishing a business architecture practice and ensuring that it becomes embedded within the fabric of an organization.

This article explores some of the circumstances that have led to rampant technical debt and offers some suggestions on how they might be averted. 

Over the past few years, the professional prestige of IT departments has declined while the use of IT keeps growing. Soon, practically all smartphones and smart TVs worldwide will connect to the Internet, and while billions of these devices and the systems that power them will go online and increase the demand for IT, my professional practice and the data from the MMVM project indicate that the influence of CIOs and IT teams is decreasing, while the frustration of organizations and clients with the IT organization is increasing. The high failure rate of IT projects persists, while obsolete systems and cybersecurity risks are on the rise. That’s why it’s indispensable to start moving IT management in a different direction — the professional and deliberate management of trust, along with continuous growth in the soft management capabilities of IT professionals that have become the new core competences of the technical professional.

One of the forces that holds enterprise architecture (EA) back from successful management of rapid change is a perspective from earlier days of the profession. A long-standing school of thought holds that architectural work at the enterprise level is best accomplished by a formal and comprehensive architectural project, which may — one hopes — be revisited periodically. However, the practice of pure “architecture projects” is antithetical to the current rapid pace of disruptive change. Architecture work measured in months and years is a relic of bygone times. What our current situation really needs is for EA to be performed by a continuous and situationally nimble process.

I was reading a press release from a large health care provider notifying customers of a potential data breach. According to the company, “a test database was inadvertently left accessible via the Internet.” Upon learning of the incident, the company secured the database and removed it from public view. It then conducted an “exhaustive investigation,” determining that the database included patients’ names, addresses, telephone numbers, email addresses, medications, and “limited” clinical information.

The rapid pace of technology innovation that characterizes the digital economy is altering established competitive landscapes, breaking industry barriers, and redefining the core parameters of customer relationships. Competing in this disruptive, digitally fueled business environment — and realizing the unprecedented growth potential of digital business — requires a level of agility and responsiveness that cannot be delivered by conventional business strategies and operating models. 

In this Executive Update, we explore the implications of four imperatives to identify the key architectural characteristics and capability foundations that define a digital enterprise. 

Leadership is absolutely critical for high-performance outsourcing. In this realm, however, it differs from the typical management narrative of a single individual who inspires and influences others. The key difference is that high-performance outsourcing requires effective leadership pairings, not a sole leadership figure. And leadership pairings between parties is not just at the top; it needs to cascade through the formal biparty hierarchy and include opinion leaders as well. This Executive Update explains leadership pairing and how it saved a contract in default.

In this on-demand webinar with Roger Evernden you'll learn what is required of architecture professionals in managing architectural evolution. Will the field naturally emerge, or will it require the intervention of architects?

Several companies have tried to enter the payment market and failed. When developing new disruptive innovations, success is about entering the market at the right time with the right product. Danske Bank launched a mobile payment application, which gained market dominance by following a disruptive "up market" path, from a simple application to a now-advanced payment platform, competing in several payment markets.

What strategies do you apply to modernizing a product code base? What results do you get with those strategies? This Advisor takes a retrospective look at a past project, both to describe the strategies my colleagues and I used to rearchitect the product and to validate the effectiveness of those strategies with two technical debt assessments via Cutter's Technical Debt Assessment and Valuation practice. 

This Executive Update examines key trends and developments impacting the market for, and the application of, data-centric security and protection technologies and practices that organizations should track in 2016 and beyond.