Low Code
It is time for another look at AI and low code as a call back to one of my previous blogs. The blog focused on how AI was helping with Low Code through the co-pilots and other capabilities.
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As long as we understand that the goal of a CoE implementation of any kind is not the case of CoE and "See you later" but really one of CoE and "see what can be better", we can cover the bases for a successful implementation of a Center
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Take a look at our most read and shared blog posts from April 2023.
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It is no surprise that tools like ChatGPT and Open AI are trending like wildfire based on the very same tools telling me that news in a non-biased way.
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Low code is often presented as the future of application development. Is it true?
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In this blog I'm going to explain how to monitor your IoT or other devices without having to open up ports, install agents or require access to your network.
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This blog will focus on business pre-requisites, maturity, approach, framework, methodology, and processing of INCQA – i.e. to ensuring the business’ right platform/tools acquisition and successful implementation and operations.
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Let's delve into some accelerated points to get us to the big decision lever and to conclude our discussion.
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Let's look at the actual Levers that help make the decision now that we understand not just what the decision being made is but why it matters more today than it did in the past.
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The key to understanding where Low Code/No Code becomes an important choice is a concept of “the Starting Point” which is essentially an acceleration to a place in the race to the finish line.
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As an Architect, you would probably be right to think that decision I make could easily affect whether or not the thing you are building would stand strong and overcome the test of time or fall apart and break with an unexpected strike at a missed weak spot.
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The purpose of this article is not to advocate or promote Low Code or its capabilities as the Panacea but, rather, to explore how to make the most out of modern tools
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Deepa Mamtani, Sogeti’s Artificial Intelligence Center of Excellence Lead in the Netherlands, observes four trends that will shape the evolution of artificial intelligence (AI) in 2022 and beyond.
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Now, before you judge me as someone with a psychological disorder–we all slow down when we see an accident on the highway, but planes crashing into each other or the ground?–let me explain why I watch these depressing films and what it has to do with IT work.
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The trend is that systems grow in complexity and that we’re relying on systems of systems to get the needed value.
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Machine learning is getting more traction. The willingness of companies to use ML models in production for their daily business is growing.
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In essence, I am very curious. That is why, whenever I see, read or hear about something that piques my interest, I do not stop until I understand it and if it finally provides me with a benefit, I do my best to include it in my portfolio. This is something that happened to me, a while ago, with DevOps.
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Kubernetes is a platform that allows containerized workloads to be managed, scaled and automated. As the ecosystem is growing more and more use cases become available.
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Cloud adoption is high from the last few years and enterprises are aggressively started their cloud journey irrespective of their size.
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A Sogeti insurance client, began a discussion around Micro Frontend Architecture and seems set on a course to bring this technology into use.
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