Need For Hyperscale And Edge Data Centers In The New Normal. The market landscape has become more competitive with only those business winning that can respond faster to the customers’ needs.
COVID-19 has been a wakeup call for businesses across the world, reminding us of the importance of embracing digital transformation in a future that will be heavily driven by automation. The market landscape has become more competitive with only those business winning that can respond faster to the customers’ needs. Adoption of Edge and Hyperscale data centres have received a lot of attention during these past months, as businesses struggle to maintain continuity, cope with changing customer requirements and look for real-time, low-cost solutions.
With everything having gone virtual, sectors such as healthcare, retail, education, gaming, social media, on-demand entertainment content have seen tremendous growth and digitalisation. A report by IDC stated that by 2025, the average person will interact with a smart device nearly 4,800 times a day, which is triple our usage today. This growing digital data necessitates faster and real-time processing to reduce market response time. Latency becomes a major factor as the majority of businesses are migrating their critical data to the cloud, that not only inhibits the ability to work efficiently, but also makes it harder to maintain a stable environment at the same time.
Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments. Our latest survey report suggests that as the overall Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments, data scientists and AI practitioners should be aware of the skills and tools that the broader community is working on. A good grip in these skills will further help data science enthusiasts to get the best jobs that various industries in their data science functions are offering.
In this article, I wish to share my thoughts on what challenging data science problems we can solve which have business value amid
The agenda of the talk included an introduction to 3D data, its applications and case studies, 3D data alignment and more.
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