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Episode 120: How to Modernize Your Data Center and Save Big with AMD
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Modernizing your data center is crucial to your organization's long-term success. In this podcast, we'll better define what data center modernization can look like for different organizations, talk through some of the ideas and promises from AMD, and offer up stories of where teams can succeed.
Host: James Hilliard
Guests: Kristin Hintlian – AMD Channel Sales Manager for Connection
Ken Bartels – Connection Technical Sales Executive for AMD (aka Resident Genius)
Show Notes:
[0:45] Modernization can mean a lot of different things to a lot of different people. What does a modern data center mean to customers?
[2:37] Are newer companies also looking to modernize due to how quickly the market is moving?
[4:40] What are some of the biggest and smallest data centers that you've been to, and how have they been able to modernize?
[7:00] What are the "people" challenges when modernizing data centers?
[11:40] Organizations are facing three big challenges surrounding data center modernization: needing better performance, reducing energy consumption, and reducing software licensing fees. How does AMD address these challenges?
[17:45] What cost savings in software licensing fees are customers seeing?
[19:35] Are there specific industries that are leading the modernization charge?
[21:50] What are some of the ways teams that have modernized with AMD have been able to push their healthcare organization forward?
[24:40] What are some examples in the manufacturing space where AMD has been able to help companies move forward?
[27:35] Walk us through some typical customer interactions in terms of how they can get an overall cost of ownership view of where they are at vs. adding new technologies.
[30:40] After the initial TCO analysis is completed, how can customers then get a good roadmap of how to get started based on their business goals?
[32:45] Reach out to your Connection account team for a TCO analysis to see what your data center modernization journey could look like.
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