For a long time, the predominant business assumption was that specialization (around markets and business functions) was the right approach to complexity (divide and conquer), efficiency, and market responsiveness (closer knows best). In a divide-and-conquer paradigm, the "pipes and filters" pattern -- with islands (or silos) of information processing, decision making, and action, and "pipes" or information buffers between -- works well enough organizationally and for the technology firmament supporting that mode of business operation.

Information technology is often called a "tool" and is compared with other tools and technologies, such as railroads, electricity, the printing press, and so on. The extension of these metaphors from the realm of molecules to information is erroneous. First, IT isn't exactly a tool. It is better described as a tool-making process. We can fashion IT in many different ways to suit all sorts of purposes.

There is no escaping the talk (and rhetoric!) about Big Data. Vendors are peddling Big Data solutions; consulting firms employ Big Data specialists to help you with your Big Data projects; universities offer Big Data courses; Big Data conferences are aplenty; and tech journalists, magazines, and even blogs are buzzing about the Big Data revolution. This is great, especially after the Great Recession we just endured. We welcome any excitement about technology buzzwords!

Every year, we hear about a shortage of talent. Many people label it a "war for talent." Well, this war has been going on for decades, with no end in sight. Is it really a war?

No. And there's data to back me up.

Best practices are prescriptive, and Agile development opposes prescription. So, in this sense, there are no Agile best practices. Managers faced with a need to impose new processes are always in search of guidance, however, and need to know that they are doing what they have set out to do -- or at least are on track to do so. Guidance, whether it is called "best practices," "good things to do," or "useful approaches," is still necessary.

I've face various challenges in my consultancy assignments. Over a decade ago I started to think of EA as a unification framework, which describes the subject of effort spent every day by countless IT professionals.

Big Data is difficult to define precisely, yet we all seem to know it when we see it.

Hadoop continues to generate a lot of attention as the Big Data platform for the enterprise. Here are the benefits and obstacles I see that organizations should carefully weigh when considering how they can employ Hadoop.

Recently there has been a spate of negative financial news in the big IT space. In some respects, this is not exactly new news. Companies like HP and Dell have had financial problems for some time, but now more mainstream organizations like Cisco, IBM, and Microsoft are all reporting falling revenues.

The world around your company has changed. What does the Internet in general -- and the latest trends of cloud computing and Big Data in particular -- mean for knowledge about your customers? The core of these changes is the amount of connectivity we now have, as individuals and as a society.

I am currently writing a series of Executive Updates about the most practical architecture frameworks and how organizations are using them (see "A Practical Guide to the Most Useful Architectural Frameworks: Part I -- The Arc

[From the Editor: This week's Cutter IT Advisor is from Matt Ganis's and Avinash Kohirkar's introduction to the October 2013 issue of Cutter IT Journal, "The Value of Social Media Data Analytics" (Vol. 26, No. 10). Learn more about Cutter IT Journal.]

There is no question that analytics has been undergoing significant upheaval as traditional BI, advanced analytics, and Big Data have come together. As we have pointed out in previous Advisors, recent attention has focused upon the velocity component, and application to real-world processes.

The economy is dragging. Even the Chinese have downgraded the US dollar. Businesses have shuttered their doors entirely over the latest words from Washington. Watch the news lately?

In the late 1880s, a set of maladies associated with the social and economic turbulence following the full impact of the Industrial Revolution afflicted many of the business, political, and upper-class elite of the US.

Data virtualization1 is touted as applicable for a range of business operations and applications, ranging from those associated with data analysis, analytics, and information management to business process management (BPM) and enterprise integration, portals, cloud services, and enterpri

In my mobile development practice, often the most challenging aspect of a project is to convince the customer that strongly held beliefs and emotional investment in a product vision can be counterproductive.

A recent Cutter Consortium survey (conducted July through September 2013) of 39 end-user organizations worldwide gives us some idea of the extent to which organizations are using NoSQL databases to support analytics.

As noted in Part I of this Advisor, the idea of riskfare itself isn't new (although I think I may be the first to use the term); the concept has been radically transformed over the last 60 years in light of the development of modern portfolio theory and behavioral economics.

One of the most influential talks of my career was an internal talk Cutter Fellow Tom DeMarco gave about 20 years ago at the company I worked for at that time. "On Beyond Zebra" was its title and it was about politics in organizations.

In a 2012 Cutter IT Journal article entitled "Business Capability Architecture Is the Tie that Binds All," Andrew Guitarte discussed how to use business capabilities to improve efforts related to business strategy, enterprise change, and project portfolio prioritization. We concur that strategy, enterprise change, and portfolio management are managed more effectively using business architecture, and agree that capabilities are a component of business architecture.

Traditional enterprises have been very interested in using Hadoop. But until recently, they have been hampered by a lack of suitable uses case for applying it.

The Middle Ages used a phrase to describe a term that was not meaningful as "a distinction without a difference." Oftentimes, in the desire to catch a technological/marketing wave, salespeople and consultants overuse terms coined to describe one thing to mean something entirely different.

We must refrain from the male altogether.

So spoke Lysistrata, the heroine main character in Aristophanes's circa 410 BC comedic play of the same name, who forms an alliance among the women of Greece in which they agree to withhold sex from their husbands until the men decide to end the Peloponnesian War.

"Context over content" is a good metaphor to keep in mind when considering a technical debt assessment, reduction, and prevention engagement. Specific patterns in your code and the intricacies of your programming environment are paramount factors in determining how general insights will be turned into actions. In other words, it is unlikely that a technical debt engagement in your company will evolve along similar lines to those taking place in your competitor's "shop" down the street.