Strategic advice to leverage new technologies
Technology is at the heart of nearly every enterprise, enabling new business models and strategies, and serving as the catalyst to industry convergence. Leveraging the right technology can improve business outcomes, providing intelligence and insights that help you make more informed and accurate decisions. From finding patterns in data through data science, to curating relevant insights with data analytics, to the predictive abilities and innumerable applications of AI, to solving challenging business problems with ML, NLP, and knowledge graphs, technology has brought decision-making to a more intelligent level. Keep pace with the technology trends, opportunities, applications, and real-world use cases that will move your organization closer to its transformation and business goals.
Recently Published
I have mixed feelings about the FBI/Apple iPhone standoff. On the one hand, due to all the data collection and spying activities revealed by former US National Security Administration (NSA) contractor Edward J. Snowden, it seems like Apple has a pretty good argument for not wanting to comply immediately with a federal court order demanding that the company develop a specialized version of its iPhone operating system (iOS) that would enable the FBI to unlock the on-device security features of the iPhone belonging to one of the San Bernardino, California, terrorists.
Localization is an inevitable requirement of mobility. However, once an individual enters a building, GPS becomes inaccessible, Wi-Fi triangulation may be unreliable, and cellular triangulation may be impossible. As we illustrate in this Executive Update, the next area of importance is indoor location, which continues to lag due to various obstacles.
In the days of large waterfall projects, organizations made the assumption that a software budget was allocated one-third per major category: analysis and design, develop, test. This was the rule of thumb that was used to generate a high-level estimate (HLE). This rule of thumb was great when it was applied evenly to all three categories. However, what usually happened on software projects is that the first two categories needed more time and it inevitably came at the expense of testing in an effort to stay on budget.
We are rapidly moving to a world where individuals don’t switch off their technologies, and companies can’t switch off their technologies. Head-up displays, image recognition, wearable technologies, virtual reality, a revolution in manufacturing technologies, the Internet of Things (IoT), super-dense computer memory … the list goes on and on! But what does this mean for the future of enterprise architecture (EA) — as a discipline, as a process, and as it informs the nature of an enterprise?
Emerging technologies and digital disruption will transform the enterprise, but they will also transform the ways in which we architect. What will this mean for enterprise architecture in general and for the role of the enterprise architect? How will EA help enterprises to collaborate with one another? What will these changes mean for the nature of the enterprise and its architecture? In this issue of Cutter IT Journal, our authors provide their practical insights and guidance on disruption and emergence and what they mean for EA.
The need for an architectural viewpoint that can rationalize and maintain coherence across the entire enterprise has greatly increased. This need is driven by the disruptive emergence of technologies, which in turn has made possible ever more complex global enterprise and trans-enterprise structures. In this article I offer guidance for how to evolve EA in a way that turns this complexity from a liability into an asset, building on 21st-century tooling and technology and a digital-generation mindset.
The smartphone is increasingly the hub for personal information and identity. People are collecting, and often willing to share, information that fundamentally changes the way that businesses interact with them. Enterprise architects can no longer be content looking at the boundaries of our own organizations. We need to model the way our stakeholders operate.
We begin this article with a case study that illustrates the challenges faced by enterprise architecture in the big data space. We then outline a new approach to enterprise architecture that we believe will help organizations better embrace the benefits big data has to offer.