The bad news is that wildfires worldwide appear to be increasing — both in frequency and intensity. The good news is that the electrical utilities are applying AI for the inspection and analysis of critical infrastructure in an effort to detect and prevent wildfires caused by extreme weather, encroaching vegetation, and infrastructure failure.

We have learned that a big part of the motivation or benefit for going to the cloud is agility. Call it flexibility or scalability if you want, but “agility” is a bit broader and evokes the principles of the Agile movement. The cloud allows you to try something, fail, and move on to something else with relatively less severe consequences. The cloud does not require you to calculate with high accuracy the amount of resources you will need, or the length of time you will need them. You should be able to scale up and down, to add and remove services, to get the latest updates, and so on — without having to do the work yourself.

Most organizations will experience a large security incident at some point. The difference between an organization that survives and thrives following an incident versus one that flounders can be summed up in one word: preparation. Athletes, emergency responders, performers, and many others practice for hours before the main event. So why do organizations not do the same for security incidents? Urgent timelines, high stress, uncontrollable events, and scrutiny from customers, regulators, press, and investors are surely good reasons to put better preparation practice in place. While many organizations have a disaster recovery and business continuity plan, few focus on preparing specifically for a large security incident. In this Advisor, we examine the preparation of a strategic incident response plan.

For almost 20 years, cloud and related technologies have been transforming entire industries. Interestingly, most of the discussions around transformation tend to focus on the technical aspects, technical solutions, platforms, and various as-a-service offerings. Although the technology perspective is very important, it’s not the most critical. Truly transformational projects require a much broader perspective. In this Advisor, we explore the impact of cloud-enabled transformation on product lifecycle, processes, and organizational culture.

The list of current and emerging technologies that could impact software development is long. However, not all of them will offer opportunities. In this Advisor, I present a list of 20 technology areas that I believe have the most potential to influence software development work performance.

Many organizations are now focusing on a hybrid cloud strategy: moving part of their IT capabilities to the cloud, while maintaining core elements in-house, hosted on-premises. The hybrid model is becoming immensely customary among orga­nizations, as it enables them to optimally allocate their resources while keeping their current IT infrastructure operating at low risk. A hybrid cloud strategy not only prepares an organization for the future but also protects its investment today.

This Advisor considers the development of a continuous deployment process for software by combining Agile methods and DevOps. After first looking at the salient characteristics of both techniques, we discuss why bringing together Agile and DevOps — and the resultant continuous delivery and deployment chain — is truly worthwhile.

Years ago, I started down the track of data democratization upon reading some Cutter Consortium Executive Reports, where the authors generally posited that if you want to manage an asset better, you must manage the data around the asset better. That may be all you have to do. But since we have to manage our companies through data, we need lots of people to do it. Hence, we need data democratization. In this Advisor, we explore how organizations can achieve data democratization.

The increasing importance of a coherent organizational strategy to maximize the exploitation of data for grow­ing a digital business is clear. There is a need to locate, consolidate, classify, and access the necessary data — often data of many different formats stored in different areas of the enterprise as well as external data — to drive many different aspects of a successful digital business. To achieve these types of capabilities in an efficient and scalable manner, the digital business needs to be able to identify, extract, transform, contextualize, and dis­tribute the necessary data. The data warehouse or data lake is a critical part of this data ecosystem, and many different aspects of the digital business can exploit this resource in a consistent way by means of a shared metadata framework.

A topic frequently raised when discussing enterprise artificial intelligence (AI) adoption trends is the issue of open source AI development tools versus commercial providers’ AI offerings. According to findings from a recent  Cutter Consortium AI adoption survey, the majority of responding organizations currently implementing (or planning to implement) AI applications are opting to use open source AI environments.

Among the most important developments concerning AI and blockchain are the new, emerging business models, enabled by these technologies, that are beginning to appear in various industries. This is especially true when it comes to fintech, and the combining of blockchain and AI to create new financial platforms that can provide virtual banking services to people who currently are not served or who are underserved by more traditional banking services offers a good example.

For almost 20 years, cloud and related technologies have been transforming entire industries. Interestingly, most of the discussions around transformation tend to focus on the technical aspects, technical solutions, platforms, and various as-a-service offerings. Although the technology perspective is very important, it’s not the most critical. Truly transformational projects require a much broader perspective. A truly successful digitization project will change a company to its core. In this Advisor, we explore the impact of cloud-enabled transformation on company culture and identity.

As in the early days of the electric utility, all major cloud providers started off with a “vertically inte­grated” direct sales model (i.e., they also played the role of cloud supplier). However, several major cloud providers have started supporting sales through an indirect sales channel, leveraging specialist partners to reach out to the many different industries that could benefit from cloud services. They have allowed those channel partners to step into the billing chain, thus creating a more unique cloud supplier role, much like those electricity suppliers that stepped into the billing chain between electricity providers and electricity consumers.

Based on our client experience, a significant opportunity to improve the business value of both enterprise architecture (EA) and Agile lies in combining their practices. Several frameworks could help in this sense, and with the right vision in mind, companies can increase their ROI for both EA and Agile. In practice, we have seen several ways in which organizations combine EA with Agile thinking and methods to break through the anti-patterns and improve results. This Advisor highlights a useful example from a Netherlands central gov­ernment client and comes down to the adoption of Agile architectural approaches described in SAFe 4.5.

Combining Agile methods and DevOps requires rethinking how you run your business, since many of the concepts collectively bundled under the Agile umbrella need to be recast in light of issues faced when combining Agile and DevOps elements that relate to scalability, readiness, delivery, deployment, and operations. This Advisor looks at 12 Agile areas that must be adjusted during a recasting effort.

Some of the more interesting developments with artificial intelligence (AI) involve its application in media and entertainment. There is a great deal of innovation underway to utilize AI in practically all aspects of media and entertainment — from content creation, procurement, categorization, and distribution to display, intellectual property (IP) protection, marketing, audience measurement, and customer service.

By learning to simply recognize complexity when we see it — and learning that we cannot engage with it through reductionism — could save ourselves a lot of pain and allow our efforts to focus on quality, rather than on trying to do the impossible. By seeking to understand complexity instead of hiding it, we can build better-quality software with less stress.

My colleagues and I have visualized a line-of-business (LOB) application as a collection of finite state machines (FSMs) that model subjects and their interactions with each other. This immediately brings some much-needed structure to our application, while at the same time allowing it to be perfectly extensible. This structure will help us to automate the generation of LOB apps, as the problem now simplifies to specifying FSMs.

Do not underestimate the pace of evolution of cloud technologies. If no one in the organization watches (and understands) the new cloud delivery technologies, you may choose the wrong one, or you may be misled by a vendor that will fail to mention a better option because the vendor does not offer it.

From internal organizational rivalries to human nature to problems with IT people, data democratization faces its own set of challenges and difficulties. By recognizing the symptoms presented in this Advisor, leaders can make the road to data democratization smoother for all involved.

Many of the principles that were developed for the data warehouse are just as relevant today when considering the evolution to a digital business. Underpinning these principles is the implicit need for the active use and management of a coherent layer of metadata. In discussing the broader digital business, it may help to delineate the various systems and applications that occupy the landscape of such a business.

Here are the Business Agility & Software Engineering Excellence articles that garnered the most feedback from Cutter Members and clients in 2018. Look for these lists from each of our four practice areas, and rediscover Cutter's most intriguing articles of the year!

Here are the Business Technology & Digital Transformation Strategies articles that garnered the most feedback from Cutter Members and clients in 2018. Look for these lists from each of our four practice areas, and rediscover Cutter’s most intriguing articles of the year!

Here are the Cutter Business Technology Journal articles that garnered the most feedback from Cutter Members and clients in 2018. Look for these lists from each of our four practice areas, and rediscover Cutter's most intriguing articles of the year!

Here are the Business & Enterprise Architecture articles that garnered the most feedback from Cutter Members and clients in 2018. Look for these lists from each of our four practice areas, and rediscover Cutter's most intriguing articles of the year!