Mastering Azure Analytics
O'Reilly Media (Verlag)
978-1-4919-5665-6 (ISBN)
Microsoft Azure has over 20 platform-as-a-service (PaaS) offerings that can act in support of a big data analytics solution. So which one is right for your project?
This practical book helps you understand the breadth of Azure services by organizing them into a reference framework you can use when crafting your own big data analytics solution.
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)
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. 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.
Chapter 1Enterprise Analytics Fundamentals
The Analytics Data Pipeline
Data Lakes
Lambda Architecture
Kappa Architecture
Choosing Between Lambda and Kappa
The Azure Analytics Pipeline
Introducing the Analytics Scenarios
Example Code and Example Data Sets
What You Will Need
Summary
Chapter 2Getting Data into Azure
Ingest Loading Layer
Bulk Data Loading
Stream Loading
Summary
Chapter 3Storing Ingested Data in Azure
File-Oriented Storage
Queue-Oriented Storage
Summary
Chapter 4Real-Time Processing in Azure
Stream Processing
Tuple-at-a-Time Processing in Azure
Summary
Chapter 5Real-Time Micro-Batch Processing in Azure
Micro-Batch Processing in Azure
Summary
Chapter 6Batch Processing in Azure
Batch Processing with MapReduce on HDInsight
Batch Processing with Hive on HDInsight
Batch Processing with Pig on HDInsight
Batch Processing with Spark on HDInsight
Batch Processing with SQL Data Warehouse
Batch Processing with Data Lake Analytics
Batch Processing with Azure Batch
Orchestrating Batch Processing Pipelines with Azure Data Factory
Summary
Chapter 7Interactive Querying in Azure
Interactive Querying with Azure SQL Data Warehouse
Interactive Querying with Hive and Tez
Interactive Querying with Spark SQL
Interactive Querying with USQL
Summary
Chapter 8Hot and Cold Path Serving Layer in Azure
Azure Redis Cache
Document DB
SQL Database
SQL Data Warehouse
HBase on HDInsight
Azure Search
Summary
Chapter 9Intelligence and Machine Learning
Azure Machine Learning
R Server on HDInsight
SQL R Services
Microsoft Cognitive Services
Summary
Chapter 10Managing Metadata in Azure
Managing Metadata with Azure Data Catalog
Summary
Chapter 11Protecting Your Data in Azure
Identity and Access Management
Data Protection
Auditing
Summary
Chapter 12Performing Analytics
Analytics with Power BI
Batch Analytics Reporting with Power BI in the Blue Yonder Scenario
A Look Ahead
| Erscheinungsdatum | 27.04.2017 |
|---|---|
| Verlagsort | Sebastopol |
| Sprache | englisch |
| Maße | 181 x 233 mm |
| Gewicht | 696 g |
| Einbandart | kartoniert |
| Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
| Informatik ► Software Entwicklung ► SOA / Web Services | |
| Schlagworte | Analytics • Cloud Computing • Microsoft Azure • Spark • Storm |
| ISBN-10 | 1-4919-5665-8 / 1491956658 |
| ISBN-13 | 978-1-4919-5665-6 / 9781491956656 |
| Zustand | Neuware |
| Haben Sie eine Frage zum Produkt? |
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