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Titlebook: Business in Real-Time Using Azure IoT and Cortana Intelligence Suite; Driving Your Digital Bob Familiar,Jeff Barnes Book 2017 Bob Familiar

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31#
發(fā)表于 2025-3-27 00:08:33 | 只看該作者
https://doi.org/10.1007/978-3-658-03962-2This chapter reviews several key security topics including threat modeling, security protocols, encryption, and key management as well as managing user identities and supporting multi-tenancy in your solution.
32#
發(fā)表于 2025-3-27 05:10:03 | 只看該作者
Real-Time Processing Using Azure Stream Analytics,This chapter examines the use of Microsoft Azure Streaming Analytics to create jobs to process the incoming data streams from various sensors, perform data transformations and enrichment, and finally, to provide output results into various data formats.
33#
發(fā)表于 2025-3-27 08:27:10 | 只看該作者
34#
發(fā)表于 2025-3-27 12:48:35 | 只看該作者
Advanced Analytics Using Machine Learning and R,This chapter explores the exciting new world of machine learning and predictive analytics. Machine learning is currently one of the most exciting technology topics in the IT industry today. With very good reason, as it being used across almost every major industry segment and vertical today.
35#
發(fā)表于 2025-3-27 16:41:00 | 只看該作者
Data Visualizations, Alerts, and Notifications with Power BI,This chapter explores the use of data visualizations, alerts, and notifications to help today‘s businesses provide useful communications to their employees and customers in order to successfully manage their operations in real time.
36#
發(fā)表于 2025-3-27 19:08:33 | 只看該作者
37#
發(fā)表于 2025-3-27 22:05:37 | 只看該作者
Bob Familiar,Jeff BarnesProvides a business case for IoT and Advanced Analytics that focuses on operational efficiencies and new revenue opportunities.Details both architecture patterns and implementation for a complete end-
38#
發(fā)表于 2025-3-28 03:05:54 | 只看該作者
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39#
發(fā)表于 2025-3-28 08:57:51 | 只看該作者
40#
發(fā)表于 2025-3-28 12:27:27 | 只看該作者
Batch Processing with Data Factory and Data Lake Store, modern business running at Internet speed. It first covers the basic technical aspects and capabilities of Azure Data Factory and Azure Data Lake. Following that, the chapter implements three major pieces of functionality for the reference implementation:
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