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Cloud analytics migration: how to exceed expectations

CIO

A cloud analytics migration project is a heavy lift for enterprises that dive in without adequate preparation. A modern data and artificial intelligence (AI) platform running on scalable processors can handle diverse analytics workloads and speed data retrieval, delivering deeper insights to empower strategic decision-making.

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The mainframe’s future in the age of AI

CIO

If there’s any doubt that mainframes will have a place in the AI future, many organizations running the hardware are already planning for it. In some cases, that may be a better alternative than moving mission-critical data to other hardware, which may not be as secure or resilient, she adds.

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9 IT skills where expertise pays the most

CIO

It enables developers to create consistent virtual environments to run applications, while also allowing them to create more scalable and secure applications via portable containers. Using this software, organizations can better streamline server hardware, with fewer physical servers on site, and still expand server capabilities.

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Gartner projects major IT spending increases for 2025

CIO

Device spending, which will be more than double the size of data center spending, will largely be driven by replacements for the laptops, mobile phones, tablets and other hardware purchased during the work-from-home, study-from-home, entertain-at-home era of 2020 and 2021, Lovelock says. growth in device spending.

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How today’s enterprise architect juggles strategy, tech and innovation

CIO

to identify opportunities for optimizations that reduce cost, improve efficiency and ensure scalability. Software architecture: Designing applications and services that integrate seamlessly with other systems, ensuring they are scalable, maintainable and secure and leveraging the established and emerging patterns, libraries and languages.

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AI chip startup Axelera lands $27M in capital to commercialize its hardware

TechCrunch

Unlike conventional chips, theirs was destined for devices at the edge, particularly those running AI workloads, because Del Maffeo and the rest of the team perceived that most offline, at-the-edge computing hardware was inefficient and expensive. ai also offer in-memory solutions for AI, data analytics and machine learning applications.

Hardware 240
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The Reason Many AI and Analytics Projects Fail—and How to Make Sure Yours Doesn’t

CIO

Many companies have been experimenting with advanced analytics and artificial intelligence (AI) to fill this need. Yet many are struggling to move into production because they don’t have the right foundational technologies to support AI and advanced analytics workloads. Some are relying on outmoded legacy hardware systems.

Analytics 205