The latest trends in learning technology mirror today's top strategic IT trends: mobile devices and applications, personalization and digital relationships, the cloud, Big Data, actionable analytics, apps, and integrated systems.

Everyone talks about social media, mobile, analytics, and the cloud (SMAC) profoundly impacting the enterprise. But while these technologies hold tremendous promise, each presents its own issues and considerations when it comes to its utilization for business.

Organizations have been developing mobile BI applications for some time now.

When developing a mobile app, especially one that is consumer-facing and is anticipated to build a large and loyal user base, agile and lean methods can be particularly valuable.

Mobile enterprise application implementation involves carefully considering how providing a select group (or groups) of employees with mobile devices and apps can achieve some business benefit.

You can break down the overall task of wrangling a project team through to enduring success into two components:

The definition and adoption of selected practices that will be used to progress through the project: the hard skills subset. Ideally, these are selected based on the nature of the project and the organizational and team culture, but are often adopted without consideration of these factors.

A revolution is coming to learning environments, with its initial impact likely to be seen in corporate training. This revolution is being fostered by Big Data analytics.

At the age of 25 in 75 BC, Julius Caesar was abducted by Cilician pirates (from modern-day southeastern Turkey) while he was sailing for Greece for further study (college, anyone?).

One of the major income opportunities I missed in my life was betting on a common budget question. If I had been given 100 Euros each time someone asked me, "How do I deal with budgeting in an agile environment?" I could probably fund a major contribution to the extinction of some terrible disease in the world.

I had an interesting discussion last week that started by talking about Big Data and ended in reflecting on the goals and skills of architecture.

At every turn it seems leaders are being told to embrace Big Data. They are urged to make "data-driven decisions" and to mine their warehouses of all the buried data gold. The problem? This is absolutely the wrong direction to go in. In a past Executive Update, Cutter Fellow Vince Kellen suggested that the problem is that leadership isn't using their data properly (see "Fighting the Metrics Glut: Keep Your Eye on Mastering Strategic Activities").

Organizations are increasingly inundated by data: more sources of data, more types of data, and more detailed data. Yet while the volume, depth, and diversity of data continue to increase exponentially, the need to cut through the growing noise becomes more challenging and ever-more urgent. Organizations will need a new type of decision maker to address this need.

During the past decade we have seen a great deal of pressure placed on environmental issues. There have been more restrictive emission norms, a somewhat sense of being forced to use renewable sources of energy, the emergence of passive buildings, and even green IT.

Stakeholders new to agile are typically delighted early in the project as they see regular demonstrations of shippable software. They are often fascinated by aspects of the process such as the efficiency of daily stand-up meetings, colorful task boards, burndown charts, and gimmicks such as estimation with planning poker cards. The simplicity and commonsense approach to planning and execution quickly win them over.

For all independent service providers (ISVs) and IT service providers, developing cloud-based services is becoming an essential business model in order to be at par with competitors and to keep infrastructure and operational cost optimal. The challenge here is two-fold: (1) developing, deploying, and maintaining services using cloud-based models form one part of the challenge; and (2) choosing the right set of infrastructure and application components and achieving a defined level of nonfunctional aspects is the other part.

So you're the new CIO? Congratulations or condolences, which should it be? A bit of both. Nobody ever said it would be easy to be a tech-savvy plus business-savvy strategist who focuses on important IT initiatives and innovations while simultaneously managing hiccup-free daily operations and delivering complex initiatives predictably, on schedule, and within budget.

But that's your job.

In Part I of this article ("Intelligent Video Analytics On the Rise, Part I"), I discussed the basics of video analytics and how the technology has evolved into comprehensive, intelligent video analysis (IVA) platforms, which are finding increasing use for automating the moni

At the time of this writing, I could find no existing laws or regulations that explicitly name Big Data within them. That could change sometime in the coming months as businesses and lawmakers realize that a variety of legal protections as well as associated information security controls are necessary to protect these digital gold mines.

A colleague and friend -- Olivier Gaudin, CEO and cofounder of Sonar -- has recently shared with me his "water leak" metaphor. The water leak metaphor asserts that resolving a technical debt situation is similar to the approach you need to take when you find water on the floor of your house.

One of my tenets of modeling is "Good enough is good enough," meaning that when a model is good enough for its intended purpose, it's time to stop messing with it.

[From the Editor: This week's Cutter IT Advisor is from Cutter Senior Consultant Jim Sutton's introduction to the April 2013 issue of Cutter IT Journal, "Is Lean the Path to Releasing the Competitiv

The Boston Marathon bombing on 15 April and the crucial role that video played in identifying and apprehending the suspects in the days after sparked my interest in examining the current state of video analytics and, in particular, new developments with intelligent video analytics (IVA) systems.

The past few months have been compelling for me in my role as a project management consultant and risk management expert.

It doesn't get much more "from the trenches" than digging in to find and fix bugs, and this is a case study based on working with a client doing exactly that. The particular issue: they were becoming increasingly unresponsive to high-priority bugs.

Many explanations and descriptions of complexity refer to, and even depend on, the notion of a system or systems. As EA also uses the notion of systems extensively, referring to systems makes it much easier to relate complexity to an EA perspective.