Designing Big Data Solutions on Microsoft Azure
summary
Covers building high-load Big Data solutions on Microsoft Azure, focusing on architectural approaches, best practices, and practical tips to avoid pitfalls. Presents cheat sheets and solution options for choosing approaches, and describes designing Rules Engines for real-time data analytics.
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chapters (15)
- 0:00Big Data introduction
- 4:00Architectural approaches
- 8:17Lambda architecture
- 14:01Big Data design best practices
- 21:49Data architecture sources
- 22:31Data migration stream processors
- 26:24Event Hubs issues
- 29:34Kafka for high loads
- 32:47NiFi connectors
- 35:57Stream Analytics
- 38:44Spark vs Storm
- 44:28Spark Storm testing
- 47:16Big Data tool selection
- 47:59Big Data security
- 50:10High availability recovery
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