Data sovereignty poses all sorts of operational difficulties for many multinational firms.

Neuromorphic computing -- computing architectures inspired by the design of brains -- is getting serious attention from large companies. IBM is placing large bets on its Watson technology and bringing applications to several industries as well as leading the way on new types of chips that implement neural networks. Google and Facebook are both applying deep learning networks in software to tagging of images, among other uses. Neuromorphic computing is rising.

In this Advisor, we focus on scalability. There are two distinct sorts of scalability: Project scalability -- addressing the ability to perform projects requiring large numbers of engineers; and Organizational scalability -- instituting common development techniques, such as Agile, consistently across an organization. While these are related, they are different. Our fundamental premise is that it is prudent to decide on a prioritization between the two.

Security is a major issue with the Internet of Things (IoT). The more devices you connect, the more you expose the organization to possible attack. And with all the reports of data breaches, system hackings, and cyber-espionage in the news, companies are naturally concerned about security when it comes to building IoT applications and services.

Watch this on-demand webinar with Tom Grant and create a value-driven ALM strategy that contributes to corporate strategy.

Automobile insurers have been capturing and analyzing data from sensor devices deployed in their customers' vehicles for some time. And the availability of such usage-based insurance (UBI) programs has grown considerably as insurance companies have expanded their in-vehicle offerings to various consumer groups (commuters, new drivers, etc.) and to commercial fleet operators.

This Executive Report examines the transformation taking place in healthcare, research, and medicine -- including key trends and developments around the application of mobile connected devices combined with cloud and big data analysis technologies applied to healthcare, fitness, and wellness programs. It also considers the benefits and issues involved in using sensor and other data acquired from personal mobile devices in conjunction with other forms of medical and healthcare data.

This Executive Report examines the transformation taking place in healthcare, research, and medicine -- including key trends and developments around the application of mobile connected devices combined with cloud and big data analysis technologies applied to healthcare, fitness, and wellness programs. It also considers the benefits and issues involved in using sensor and other data acquired from personal mobile devices in conjunction with other forms of medical and healthcare data.

The growing use of personal fitness trackers, smart watches, connected medical devices, and a myriad of sensor-enabled apps running on smartphones is also generating vast amounts of health data about consumers. For the most part, this data has not been used to any real extent by healthcare providers, clinicians, and researchers to promote the overall health and well being of patients and consumers. This is changing, and we are seeing a revolution in healthcare with the application of mHealth ("mobile health") technologies and practices.

The growing use of personal fitness trackers, smart watches, connected medical devices, and a myriad of sensor-enabled apps running on smartphones is also generating vast amounts of health data about consumers. For the most part, this data has not been used to any real extent by healthcare providers, clinicians, and researchers to promote the overall health and well being of patients and consumers. This is changing, and we are seeing a revolution in healthcare with the application of mHealth ("mobile health") technologies and practices.

Only 100 years have passed since the Industrial Revolution and we are already in the midst of a new revolution, the latest being of a digital nature.

Both the Lean and Agile worlds encourage and value learning by doing. The Scrum framework pushes teams to engage in an ongoing PDCA (Plan-Do-Check-Act) cycle to continually inspect and adapt how they work and how they develop software.

For Scrum teams, the end-of-sprint review is where they inspect the increment of work they created during the iteration and examine what they have learned about their deliverables. Based on this knowledge, teams can review their upcoming backlog items and adjust when they feel it is necessary.

One of my first tasks upon joining the EA team at Syngenta, a multinational agribusiness company, was to redefine the global architecture governance processes. Among my first tasks after joining the EA team at Syngenta was to redefine the architecture review board (ARB), a need that was triggered by a review of our enterprise architecture program.

The distinctive features of cloud computing offer many potential opportunities for business innovation, particularly given its service (and service quality) focus, coupled with the flexibility that new technology delivery mechanisms provide. However, our most recent research finds good reasons for qualifying the assumption of frictionless innovation arising from cloud adoption. The pattern, instead, may well follow past diffusions of other potentially powerful technological innovations, including the Internet itself.

The distinctive features of cloud computing offer many potential opportunities for business innovation, particularly given its service (and service quality) focus, coupled with the flexibility that new technology delivery mechanisms provide. However, our most recent research finds good reasons for qualifying the assumption of frictionless innovation arising from cloud adoption. The pattern, instead, may well follow past diffusions of other potentially powerful technological innovations, including the Internet itself.

To be faster and cheaper, DevOps should integrate currently separated QA tasks -- from testing done during development to monitoring executed on daily operations routines -- under a common, business-oriented, and actionable QA architecture, designed and built into IT systems. This Executive Report offers such an architecture pattern for IT service assurance.

To be faster and cheaper, DevOps should integrate currently separated QA tasks -- from testing done during development to monitoring executed on daily operations routines -- under a common, business-oriented, and actionable QA architecture, designed and built into IT systems. This Executive Report offers such an architecture pattern for IT service assurance.

The latest trends, including DevOps, prove that we must extend quality assurance (QA) efforts to the operations and maintenance period, and we must focus them on the services provided by IT. QA work also involves the amount of time and money spent, right? Not necessarily.

The latest trends, including DevOps, prove that we must extend quality assurance (QA) efforts to the operations and maintenance period, and we must focus them on the services provided by IT. QA work also involves the amount of time and money spent, right? Not necessarily.

Back in 1887, Mark Twain noted that, "All you need in this life is ignorance and confidence, and then success is sure." We've recently had two primary examples of senior organizational management who seem to be following Twain's advice with extra zeal.

Traditional computer networks are complex and very hard to manage (see "Unraveling the Complexity of Network Management"). To express the desired policies, network operators need to configure each individual network device, one by one, either manually or with the use of low-level scripts. In addition to configuration complexity, network environments have to endure the dynamics of faults and adapt to load changes. Enforcing the required policies in such a dynamic environment is highly challenging.

In this Executive Report, Part II of a series on cloud computing, we explore the effective adoption and management of the cloud by small and medium-sized enterprises (SMEs) as well as global leading firms. Using case examples, we demonstrate, in detail, the challenges and practices used with these types of organizations. We also provide three distinctive lessons for SMEs and 10 lessons for all organizations.

In this Executive Report, Part II of a series on cloud computing, we explore the effective adoption and management of the cloud by small and medium-sized enterprises (SMEs) as well as global leading firms. Using case examples, we demonstrate, in detail, the challenges and practices used with these types of organizations. We also provide three distinctive lessons for SMEs and 10 lessons for all organizations.

Cloud computing is considered the great equalizer between small and large client firms by many senior executives and pundits. Is this true? And what are the emerging practices and lessons from cloud adoption by SMEs? To answer these questions, we describe three illustrative cases in depth: the Dana Foundation, Diesel Direct, and Art-World.

Cloud computing is considered the great equalizer between small and large client firms by many senior executives and pundits. Is this true? And what are the emerging practices and lessons from cloud adoption by SMEs? To answer these questions, we describe three illustrative cases in depth: the Dana Foundation, Diesel Direct, and Art-World.