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Real-Time Data Stream Processing in Azure
Delve into big data streaming with Azure using Event Hubs, Data Lake, and Azure Stream Analytics About This Video Learn to think of data as an ever-flowing stream of events Discover how to harness the power of data events using Azure Stream Analytics Get up to speed with Azure Event Hubs In Detail A...
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| Formato: | Electrónico Video |
| Idioma: | Inglés |
| Publicado: |
Packt Publishing,
2020.
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| Edición: | 1st edition. |
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| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
| Sumario: | Delve into big data streaming with Azure using Event Hubs, Data Lake, and Azure Stream Analytics About This Video Learn to think of data as an ever-flowing stream of events Discover how to harness the power of data events using Azure Stream Analytics Get up to speed with Azure Event Hubs In Detail A modern digital company captures a large amount of data every day. This data gets locked in data islands such as caches, queues, and logs, and extracting this data and making it useful poses a major challenge. Real-time data processing is the most effective alternative to traditional extract, transform, and load (ETL) processes. This course will help you to think of data as an ever-flowing stream of events instead of data as islands locked away in databases. This course employs live labs to get you up to speed with Azure Event Hubs and teach you how to create C# console applications for sending and receiving data from Event Hubs. As you advance, you'll learn how to capture and archive data from Azure Event Hubs to Azure Data Lake. The subsequent videos will show you how to provision Event Hubs, Data Lake, and SQL Server databases in Azure. Toward the end of the course, you'll write an analytics job to stream live data from an event hub to a SQL Server database. By the end of this course, you'll have developed a solid understanding of how to stream big data using Azure Stream Analytics. |
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| Descripción Física: | 1 online resource (1 video file, approximately 1 hr., 15 min.) |