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 data-centric security model focuses on protecting an organization's sensitive data as opposed to protecting the overall computer networks and applications — as is the case with more traditional security models that function primarily by implementing a security perimeter designed to keep bad actors out. That said, data-centric security is intended to support an organization's overall data loss prevention strategy in conjunction with network, anti-virus, and other enterprise security incident and event management systems.
Providing an enterprise-wide data store has been one aim of the enterprise data warehouse since the 1990s. One of the key lessons learned was that resolving issues of meaning and context — metadata — was central to any successful implementation. The challenges remain: very few data warehouse teams have claimed anywhere near complete success. It is also interesting to note that these issues have, finally, been recognized by data lake proponents. Tools offering big data governance, data wrangling, and similar function have begun to emerge over the last year or so. Unfortunately, once again, the tools precede an understanding of the true extent of the problem: how to traverse from data and information to knowledge and finally meaning and vice versa?
I would like to broaden the conversation around technical debt to include the challenges of keeping up with software vendors’ lifecycles. Such vendor-driven technical debt requires the continual attention of CIOs and technology executives, who need to balance limited budgets to cope with technical debt. In this article, we will examine aspects of the problem and evaluate some of the techniques to address and repay technical debt.
This article will present the key concepts of the SQALE method and explain how to use it, either in a day-to-day context (as, for example, within an Agile project) or at corporate level to govern a portfolio and optimize its technical debt.
If there is rampant technical debt with most software products and services, why don’t organizations do something about it? Well, it’s complicated. Let’s take a step back and look at what we mean by technical debt and how we can measure it. Then let’s take a longer look at why technical debt exists and what you can do to address it.
Many long-standing problems like technical debt owe their longevity to two factors — not dealing effectively with their causes and not dealing effectively with their resilience. Because what limits our ability to deal with technical debt might be not be technical, it is useful to explore possible psychological and political sources of the longevity of the technical debt problem.
In a recent Cutter IT Journal (CITJ) article ("Leveraging EA to Incorporate Emerging Technology Trends for Digital Transformation"), Cutter Senior Consultant and esteemed colleague Bhuvan Unhelkar and I presented our practical experience in leveraging EA to incorporate emerging technology trends for digital transformation. In the article, we shared the following steps that EA as a discipline can use in facilitating digital transformation:
Content management is a fundamental building block of your digital business strategy. Digitization and the potential it offers for streamlined, efficient, and lower-cost management of content is extensive and largely untapped. Enterprises that want to ride the wave of digital transformation must develop a robust model for content management. The roadmap outlined in this Executive Update is a key enabler for enterprises to implement healthy digitization and simplification.