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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If we can stay focused on the intent and spirit behind the words “agile” and “architecture,” maybe we can avoid the cycle of hype and despair, at least as far as agility is concerned. This requires discipline with both words and actions because they are both part of the real world.
In today’s business environment, it’s rare to speak with an enterprise leader who is not adopting some form of Agile development practice. Indeed, global companies of every size are adopting Agile practices and principles. However, traditional Agile does not consider enterprise architecture (EA) as a key part of the process and only assumes that architecture guidance is being provided in the background. As we explore in the accompanying Executive Report, EA leaders who have identified the need to change in light of the emergence of Agile have significant opportunities to help Agile projects move more quickly and be more effective.
In today’s business environment, it’s rare to speak with an enterprise leader who is not adopting some form of Agile development practice. Indeed, global companies of every size are adopting Agile practices and principles. However, traditional Agile does not consider enterprise architecture (EA) as a key part of the process and only assumes that architecture guidance is being provided in the background. As we explore in this Executive Report, EA leaders who have identified the need to change in light of the emergence of Agile have significant opportunities to help Agile projects move more quickly and be more effective.
Self-service BI can lead to increased, widespread dissemination of BI/analytics tools and practices across the organization; in effect, helping to promote a data-driven culture. It allows employees of all types — at least in theory — to more easily locate, access, and work with a range of information and data. This is accomplished in several ways, including via highly visual, intuitive self-service BI tools and automated data preparation and workflows that provide advice on various steps of the analytical process.
The idea that an organization should change from a particular language, such as one of those named above or any of the myriad of others that may be currently in use, to find DevOps success is a slippery slope and is not necessary to implement the DevOps principle of increased deployment frequency. Any language will work well with the right principles and practices in place.
Interest in smartbots and intelligent virtual assistants employing AI, natural language processing (NLP), speech recognition, and other cognitive techniques for automating and enhancing customer interaction and experience is increasing.
Harmonization is a cloud provisioning and procurement decision-making approach relevant to every enterprise cloud buyer with large, complex, or sophisticated cloud computing needs. The organizations most likely to realize the long-term benefits of this new method are typically those with increasing cloud usage, particularly organizations with several long-term projects. This method is a collection of strategies designed to mitigate and manage the oft-overlooked cost impact of cloud sprawl. It provides oversight and influence back to enterprise IT, while minimizing the loss of developer agility in rapidly provisioning suitable cloud resource. Once implemented, it engenders a coordinated, sustainable approach to cloud procurement that reduces costs, improves governance, and allows for efficient procurement without compromising business agility.
Farmers and the agricultural companies that service their needs deal with vast amounts of structured and unstructured data. Analysis of such data gathered from across a variety of growers and growing conditions, combined with data from other sources — including satellite and drone imaging, field-level sensors, weather, and other historic data — can provide insights to enable farmers to make timely decisions that can improve their yields and minimize losses due to unpredictable changes in weather.