Real World Big Data in Azure
MP4 | AVC 336kbps | English | 1024x768 | 15fps | 5h 21mins | AAC stereo 93kbps | 758 MB
Genre: Video Training
How do you make sense of Big Data? When youre receiving 100 million events per hour and you need to save them all permanently, but also process key metrics to show real-time dashboards, what technologies and platforms can you use? This course answers those questions using Microsoft Azure, .NET, and Hadoop technologies: Event Hubs, Cloud Services, Web Apps, Blob Storage, SQL Azure, and HDInsight. We build a real solution that can process ten billion events every month, store them for permanent access, and distill key streams of data into powerful real-time visualizations.

Understanding Big Data in Azure
Introducing Big Data in Azure
Is This Course for Me?
Building the Phase 1 Solution
Evolving the Phase 2 Solution
Introducing the Telemetry API
Demo: EventsController
Key Features of the Telemetry API
Zipping the Event Batch
Demo: GZipToJsonHandler
Testing the API
Demo: IEventSender
Module Summary

Ingesting Data into Event Hubs
Module Introduction
Introducing Event Hubs
Configuring Event Hubs
Creating Event Hubs
Automating Event Hub Creation
Sending Events
Demo: EventHubEventSender
Batching Events
Demo: EventBatchIterator
Batching and Testing
Demo: Acceptance Tests
Understanding Throughput Units
Demo: Deploy, Monitor & Scale
Next Steps for Deployment & Monitoring
Isolating the Event Hub
Module Summary

Storing Event Data for Batch Queries
Module Introduction
Aim of Deep Storage
Concurrency and Partitions
Demo: IEventProcessor
Competing Consumers
Buffering Output
Demo: DeepStorageEventProcessor
Level 1: In-Process Memory
Demo: MemoryEventStore
Level 2: Local Disk
Demo: DiskEventStore
Level 3: Blob Storage
Demo: BlobStorageEventStore (Part 1)
Demo: BlobStorageEventStore (Part 2)
Timed Flushing
Demo: Deep Storage Worker Role
Scaling Read with Throughput Units
Module Summary

Querying Batch Data in Deep Storage
Module Introduction
About Pig
Demo: AzCopy and Pig
Importing Libraries
Demo: Pig and JSON Data
HDInsight and Pig
Demo: Running Pig Scripts in HDInsight
Streaming Data to Commands
Demo: Streaming from Pig to .NET
Visualizing Output from Pig
Demo: Visualization with D3.js
Module Summary

Normalizing Event Data for Real-Time Queries
Module Introduction
Modeling Event Metrics
Demo: Building the Data Model
Refactoring the Event Receiver
Demo: Core.EventProcessor
Dependency Injection and the EventProcessorHost
Buffering in the Event Handler
Demo: ModelBuffer of T
Handling Event Metrics
Demo: EventMetricsHandler
Running On-Premise
Demo: RealTime.WorkerRole
Running in Azure
Demo: Azure Deployment
Module Summary

Building Real-time Dashboards
Module Introduction
Demo: Installing
About Widgets
Demo: The Number Widget
About Scheduled Jobs
Demo: Event Count Job
How Dashing Pushes Updates
Adding New Widgets
Demo: The Pie Widget
Running Dashing on Azure
Demo: Deploying Azure Web App
Demo: Securing the Web App
Module Summary

Using Storm for the Plumbing
Module Introduction
Spouts, Bolts, and Topologies
Parallelism in Storm
Demo: The Event Hub Spout
Demo: Connecting to the Event Hub Spout
Topology for Event Metrics
Demo: Event Metrics App
Storm and HSInsight
Demo: Running in Azure
Module Summary

Using HBase for Storage
Module Introduction
About HBase
Modeling Device Errors in HBase
Demo: HBase on HDInsight
HBase Row Key Design
Demo: Device Errors in Storm
Demo: Device Errors in HBase
The HBase .NET SDK
Demo: Dashing and HBase
Module Summary
Course Summary

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