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Some Considerations To Think Of When Pursuing Big Data Initiatives Video

by Dr Mark van Rijmenam•
Intel Data Center GPU codenamed Crescent Island architectural slide showcasing Xe3P AI optimized GPU IP, up to 480GB LPDDR5x memory capacity, and a 350W air-cooled PCIe form factor.
Intel’s Crescent Island GPU targets AI inference economics by prioritizing massive LPDDR5x memory capacity over costly HBM architectures within a practical 350W air-cooled design.

Building confidence in big data and information is important when developing a big data strategy. Gaining an understanding of the underlying data that is used is very important to have confidence in using the data. The data has to be governed to ensure that it is clean and can be used. There are several considerations to achieve a level of confidence and one of them is knowing where the data came from.

The second thing is to know what has been done with the data during processing the data. Of course also the privacy and security issues surrounding the data need to be thought about upfront instead of afterwards. Claudia Imhoff, president of Intelligent Solutions and founder of Boulder BI Brain Trust, talks with David Corrigan, director of IBM InfoSphere product marketing, about the considerations that organizations should think about when trying to achieve this level of confidence, which ultimately will help lead to project success.

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