GE has offered its Predix software platform for building industrial Internet and Internet of Things (IoT) applications for several years now. And GE has used Predix to build custom applications for its industrial clients, as well as to develop a line of industry and domain-specific IoT solutions it markets to customers. 

There are changes ... lying ahead in every road And there are new thoughts ... ready and waiting to explode When tomorrow is today ... the bells may toll for some But nothing can change the shape of things to come

"The Shape of Things to Come" -- Max Frost & The Troopers

In our previous Advisor in this series (see "Implementing the Integrative Framework, Part II -- Scalability"), we differentiated project scalability from organizational scalability. Project scalability addresses the ability to perform projects requiring large numbers of engineers; whereas organizational scalability is about instituting common development techniques (such as Agile) consistently across an organization. Both are important, but one should not be confused with the other. You need to consider quite distinct aspects, and initiate quite different actions for each. As discussed in the previous Advisor, we recommend that at any point in time you pursue only one of the two kinds of scalability.

In addition to the various consumer technology, enterprise IT, medical device manufacturers, and other health-related companies, there are a slew of startups that are focusing on developing mobile apps, wearable devices, smart clothing, and telemedicine services designed to support consumer-centric healthcare.

Human society is currently sitting at the dawn of digital revolution led by the evolution of a new and intelligent species: digital intelligence. The real question we need to ask ourselves is are we confident of retaining the supremacy of human intelligence forever? Or is it about time we start making note of the newer intelligent species and make efforts to tame it while it is still in its infancy?

EA governance provides a common vision of the future, shared by all stakeholders, and guides in the selection, creation, and implementation of solutions driven by business requirements. It also serves as a means to control the growing complexities of technology by setting enterprise-wide standards for IT that can be leveraged. This Advisor discusses the critical, key roles that EA governance plays for transformation programs to be successful.

This interview with Bart Baesens takes a quick look at some of the issues covered in his new book "Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques: A Guide to Data Science for Fraud Detection," written with Véronique Van Vlasselaer and Wouter Verbeke. 

In this day of technological sophistication, citing a router outage as the cause of a major failure is akin to a student explaining that "the dog ate my report." If the world is going to be depending on the Internet, it is going to have provide a management and communications capability that is worthy of its new-found charter.

Today you see "impediment management processes" defined at the enterprise level, usually based on Excel spreadsheets or your favorite trusted ticket system. Sometimes managers feel that it takes too long in their organization to remove impediments, so they set up an impediment Kanban system to reduce the lead time of the impediment removal. Am I the only one who thinks that something is wrong here?

Enterprise architecture (EA) has floundered in recent years as the topography of information technology itself has changed. We have moved into a more complex environment that is less easily subject to the kinds of rigid controls envisioned in the architecture concept. We have come to view EA as a static collection of plans and descriptions that do not directly correspond to business requirements. While numerous attempts have been made to salvage its image, the basic approach itself has been subject to questions of relevance.

This article discusses intelligent apps that offer good examples of how cognitive computing and other advanced analytics technologies can be applied to help organizations redefine customer engagement and assist both consumers and employees with making complex decisions.

The IT industry struggles to deliver quality, and the majority of effort related to quality improvement is directed toward internal IT processes, rather than the results (i.e., the services) seen by customers.

Anyone who is great, as in best in the world at what they do, is both highly passionate and disciplined about what they do. Applying your passion in business is certainly a bit more complicated than doing so for a hobby. The passion must be aligned with innate or developed skills that give you a chance to be best in the world at your work.

Architecture representations must provide insights that take the enterprise forward, rather than seducing anxious business minds into illusory paths. While we do need to guard against the baser human emotions from hijacking the truth, it is also important to realize that integrity is threatened on a different front: a cognitive one.

The overall cloud computing market is now growing rapidly. There are credible estimates that the global cloud computing market could be as much as US $84 billion by the end of 2015, and will reach $241 billion in 2020 (it was $15 billion in 2010).

The growing ability of big data to seek patterns within immense data streams; perform predictive analysis; and understand language, voice timbre, sentiment, and other attributes thought to require human intervention, raises special concerns.

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.

The Internet of Things promises to eliminate massive information gaps about real-time conditions on the factory floor that have made it impossible to fully optimize production and eliminate waste in the past.

-- O'Reilly's David Stephenson

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.

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.