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The problem comes in the business world. It’s also comforting to know that many of them may be avoided with the correct tools. Process behavior charts can help with this. They are employed in a wide range of sectors, particularly in manufacturing, to determine if a process is stable

Is your CFO requesting cost-cutting measures from you? Many of the Chief Technology Officers (CTOs) I talk with are concerned about this. After all, the US is experiencing 8.5 percent inflation, which means increased input costs for businesses. This includes employees: according to Skillsoft, the number of IT decision-makers

Artificial intelligence can now without a doubt make a significant difference within a company, from addressing complex challenges to fundamentally changing a business model. That’s why, two years ago, Microsoft established AI Business School to give advice to important decision-makers across sectors on strategy, culture, responsibility, and other vital

Marc Andreessen saw that software was consuming the world a little over a decade ago. We can clearly update his quote: “Software ate the world.” The software has taken over our businesses and how we create value for our consumers. Consider this: We are a software factory, and we are

Containers, software-defined wide-area networking, cloud edge communications, and white-box devices Compared to dedicated bare-metal solutions, containerized Software-Defined Wide Area Networking (SD-WAN) on white-box x86 platforms offers a higher degree of flexibility and similar performance — especially when the goal is to deliver dynamic edge compute solutions with more outstanding security capabilities.

Agile principles, which were once largely used in the computer industry, are now being adopted by a wide range of businesses. It is a massive worldwide movement. The desire to become more agile has impacted practically every organization, just as digitization has. A snapshot of the benefits Agile methodologies enable

Most data science experiments begin with a few data files on a laptop and then use algorithms and models to anticipate a result. Although the method requires little initial computing, data scientists rapidly learn that their workloads demand more computational power than a local CPU or GPU can give. As