Über dieses E-Book
You’ll not only be able to determine which service best fits the job, but also learn how to implement a complete solution that scales, provides human fault tolerance, and supports future needs.
- Understand the fundamental patterns of the data lake and lambda architecture
- Recognize the canonical steps in the analytics data pipeline and learn how to use Azure Data Factory to orchestrate them
- Implement data lakes and lambda architectures, using Azure Data Lake Store, Data Lake Analytics, HDInsight (including Spark), Stream Analytics, SQL Data Warehouse, and Event Hubs
- Understand where Azure Machine Learning fits into your analytics pipeline
- Gain experience using these services on real-world data that has real-world problems, with scenarios ranging from aviation to Internet of Things (IoT)
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Autoren-Profil
Zoiner Tejada has more than 17 years of experience consulting in the software industry as a software architect, CTO, and start-up CEO, with particular expertise in cloud computing, big data, analytics, and machine learning. He was among the first to receive a Microsoft Azure MVP (“Most Valuable Professional”) designation and has since been awarded the MVP for five consecutive years, and now holds a dual MVP in Microsoft Azure and Microsoft Data Platform. He received his BS in computer science from Stanford University. Zoiner is the author of Mastering Azure Analytics published by O'Reilly (which covers a broad range of analytics solutions from real-time processing with Storm, to Interactive/Batch processing with Spark, the application of Machine Learning and many other Data/Analytics related Azure services). He is also co-author of Exam Ref 70-532: Programming Microsoft’s Clouds (the official exam study guide for developers seeking Azure certification), co-author of Developing Microsoft Azure Solutions, and creator of the “Google Analytics Fundamentals” course on Pluralsight.com.
