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Azure masterclass : analyze data with Azure Stream Analytics /
"For some time now, and with the boom of the Internet and social media, data is playing an increasingly bigger role in all organizations, which are continuously looking for solutions that will enable us to capture data from different internet sources, and analyze it in an as close to real-time...
| Clasificación: | Libro Electrónico |
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| Formato: | Electrónico Video |
| Idioma: | Inglés |
| Publicado: |
[Place of publication not identified] :
Packt Publishing,
2018.
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
| Sumario: | "For some time now, and with the boom of the Internet and social media, data is playing an increasingly bigger role in all organizations, which are continuously looking for solutions that will enable us to capture data from different internet sources, and analyze it in an as close to real-time rate as possible. This has caused organizations to invest in building solutions that can not only obtain and review data in depth and in real-time, but also save time in scheduling recurrent tasks and integrate with other systems seamlessly, allowing for scalability and availability while minimizing faults and latency. Having the right information in time is a now a critical aspect to making strategic business decisions. This is where Azure Stream Analytics comes in, to provide an effective solution to this business need. Azure Stream Analytics, or ASA, is an independent, cost-effective, and near real-time processing agent that enables you to view and explore streaming data at a high-performance level. Using this portal, you can set up data streaming computations from devices, sensors, websites, social media, applications, infrastructure systems, and more with just a few clicks. Do you know what it takes to design and deploy sophisticated data analytics pipelines which can transform data into actionable insights and predictions in near real-time? How does one go about scaling this data analysis infrastructure? How to easily develop and run massively parallel real-time analytics on multiple IoT or non-IoT streams of data using a simple SQL like language? These are some of the fundamental problems data analysts and data scientists struggle with on a daily basis."--Resource description page |
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| Notas: | Title from resource description page (Safari, viewed March 4, 2019). |
| Descripción Física: | 1 online resource (1 streaming video file (3 hr., 11 min., 16 sec.)) |