First published on MSDN on Nov 07, 2018 We'll continue to explore the Azure Data Architecture Guide with our third blog entry in this series. The entries for this blog series are:
Like the previous post, we'll work from a technology implementation seen directly in our customer engagements. The example can help lead you to the ADAG content to make the right technology choices for your business.
Go beyond historical reporting and exploratory analysis of your data by enabling predictive processing and automated decision making with Azure services like Azure Machine Learning and Apache Spark on HDInsight . When you need to harness the power of multiple GPUs to build sophisticated deep neural architectures and train them on a large data set, get a jump start on the task with Deep Learning Virtual Machines and CNTK , the unified deep-learning toolkit by Microsoft. See also this deep learning sample architecture .
Please peruse ADAG to find a clear path for you to architect your data solution on Azure:
Azure CAT Guidance "Hands-on solutions, with our heads in the Cloud!"
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