In practice, content and information management systems today haven’t fulfilled their promise. They don’t understand unstructured data, and they can’t directly act upon it. They work well only when people follow defined information governance processes.

One of the hardest things to teach or learn is self-awareness. By self-awareness, I mean the capacity to evaluate oneself accurately from the perspective of others and the ability to detect differences between our behavior and our values. So many leaders are unaware of what others around them truly think about them and at some point in these leaders’ careers, this inevitably leads to trouble. Usually these troubled leaders are constantly interpreting the world around them into their internal logic, thus preventing them from seeing the gap between their own internal understanding of themselves and what others think.

This article addresses the challenge of slicing data warehousing and business intelligence (DW/BI) user stories into small, business-valued deliverables to align with the Agile principle of "Deliver[ing] working software frequently, from a couple of weeks to a couple of months, with a preference to the shorter timescale."

The idea of a metaframework isn’t really anything new. It is simply a way of describing something that enterprise architects need to do.

We hope you will find the five articles on IoT in this issue of CITJ interesting, challenging, and practical. We also hope they will encourage you to experiment with the ideas they present in your own approach to integrating IoT within your business systems and processes. Needless to say, the data generated through IoT-based devices is indeed vast, unstructured, and changing rapidly — all the characteristics of big data. We see this issue as a major contribution to the literature on IoT, with overlaps in identifying the context, incorporating IoT in applications, and merging it with EA. As always, we welcome your comments on these articles.

Last week, Microsoft moved to beef up its own IoT offerings by buying IoT platform and services provider Solair. I like this deal because it gives Microsoft — which has been heavy on technology but short on actual IoT user stories — a company that can point to a good customer base with actual deployed IoT applications across various industries. Acquiring Solair, Microsoft also gets IoT hardware and IoT industry expertise, along with focused applications.

While the rise of financial technology companies and services has been gradual and steady over the years, beginning perhaps with the founding of PayPal in 1998, there’s been a particularly explosive boom in this sector just in the past couple years, with a new FinTech startup sprouting up nearly every week and disrupting the financial game in a major way. Indeed, companies like Stripe, Intuit’s Mint, Payoneer, and even such developments as Apple Pay are offering an array of fundamental changes in the many ways consumers and small businesses interact with their finances.

A frequent complaint we hear from Agile teams is that their self-organization is not respected and their manager routinely overrules their decisions. If you talk to the manager, he or she complains that the team doesn’t respect company policies anymore and makes decisions they’re not entitled to make. What seems to be a battle about power in many cases and like a confusion of self-organization with autonomy turns out to be an unfinished Agile integration into the organization.

In a recent Advisor, we called out an important function of architects: “to grapple with the elements of the enterprise that are disproportionate in their influence, and make them deliver [business value].” What is implicit in that statement is a recognition that “grappling” occurs because complex situations demand that we make the right tradeoffs and choices. It’s all about decisions. Who makes these decisions?

In my research pertaining to trends and developments influencing the market for, and the application of, data-centric security and protection that organizations will want to keep abreast of in 2016-2107, I have explored database threat protection solutions. These facilitate the discovery of all databases in the network (including those undocumented) and continuous monitoring of databases to identify malicious activity. New products employing machine learning (ML) and behavioral analysis to protect databases and facilitate real-time identification of compromised database credentials are available.

Somewhat like the data warehouse architecture before it, data lake thinking has focused mainly on the information/data contained therein — its types and structures, its modeling and usage, and so on. However, as we showed in Part II of this Advisor series, the IDEAL conceptual architecture emphasizes that information is only one of three spaces that require consideration. As we saw in that Advisor, process and people demand equal consideration. In Part IV, we discussed the aspects of process that deal with getting data into the lake and ensuring its internal consistency where required. This Advisor examines the other aspects of process: particularly choreography, as well as its supporting function of organization — the means of creating and managing all the processes of the data lake. We also briefly touch on utilization, which represents the applications that make use of the information to provide business value.

Many large enterprises struggle with annual project budgeting cycles; big up-front planning; arduous governance, portfolio, program, and project management and control mechanisms; and other systemic efforts that, while intending to establish more predictability/control and less risk, often do just the opposite. This can cause Agile initiatives to falter or to collapse under the weight of an unrelenting command-and-control mindset.

The truly game-changing opportunities or challenges we face in our businesses are a blend of the complicated and the complex. Being able to understand the difference between the two domains and manage accordingly is thus the key to success. An inability to differentiate between complicated and complex leads to one of the most fundamental causes of business and technology failure — the illusion of control.

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.

If you are considering how to leverage your unstructured data by adding intelligent search and content management to your enterprise content management platform, a good place to start is with a proof of concept (POC). Design your POC around a specific, measurable set of objectives. These objectives should cover a product’s primary content analysis function and how it meshes with your needs.

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.

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.

If not managed well, technical debt can lead to major challenges for organizations resulting in increased development and maintenance costs and reduced business agility, hindering innovations in the organization. With the speed at which digital technology is exploiting the markets and its pressing need for adoption, technical debt is adding even more challenges to organizations.

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.

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.

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.

Architectural representations often depict not the things and people in the real world, but rather the inferred characteristics and properties of those, so the representations themselves are one step removed from things and people.

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.