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.
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The “one size fits all” era, where RDBMSs were used in nearly any data and processing context, seems to have come to an end.
We call out the hardware, the software, the applications, the information, and even the business processes, as we visualize the different layers of the enterprise. However, we stop just short of defining the enterprise stack fully; what is noticeable by its absence is the most important part of the enterprise: the people.
Banking and financial services companies were among the first to apply artificial intelligence (AI) in strategic applications. Initially, this took place in the mid- to late 1980s in the form of expert and knowledge-based systems for credit and loan approval and mortgage processing, and so on, and then in the early to mid-1990s, when neural network-based applications for credit and bank card fraud detection, and profitability management, began to be deployed.
In this Update, we examine some of the more temporal aspects of using the ADF activities as part of a systems development process. We begin by revisiting the ADF activity structure and, by choosing an example development process, examine how the activities that comprise that process exchange information. We shall then look at the viability of a typical development sprint timescale in being able to accommodate all the activities necessary for large, complex development involving business analysis.
Cutter Consortium is conducting a series of surveys on how organizations are adopting, or planning to adopt, artificial intelligence (AI) technologies. We also seek to identify important issues and other considerations they are encountering or foresee encountering in their efforts. Here in Part V, we look at findings pertaining to the industries and domains where organizations see AI having its most significant impact.
In this on-demand webinar, Cutter Consortium Senior Consultant Frank Contrepois shares advice, forged from his experiences with AWS, on how you can avoid wasting money on cloud services by keeping an eye on — and acting upon — three things.
Organizations should focus their attention not on integrating, storing, or even analyzing data, but on the effective use of time.
Miklós Jánoska provides a perspective on how we can shift architecture from a governor to more of an enabler.