Business in Real Time Using Azure IoT and Cortana Intelligence Suite Driving Your Digital Transformation 1st Edition by Bob Familiar, Jeff Barnes ISBN 9781484226506 148422650X

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Product details:
ISBN 10: 148422650X
ISBN 13: 9781484226506
Author: Bob Familiar, Jeff Barnes

Business in Real Time Using Azure IoT and Cortana Intelligence Suite Driving Your Digital Transformation 1st Edition Table of contents:

Chapter 1: Business in Real-Time

A Platform Approach

Real-Time Business Platform

Methodology: Lean Engineering

Process: DevOps

Architecture: Microservices

Platform: Cloud

Internet of Things (IoT) and Big Data

The Tipping Point

Big Data

Advanced Analytics

Real-Time Business Reference Architecture

Devices

Device Hub

Stream Processing

Data Management, Storage, and Messaging

Advanced Analytics

Microservices and API Gateways

Visualization, Alerts, and Notifications

Identity

Automation

Security

Microsoft Azure IoT and Cortana Intelligence Suite

Automation

Security and Identity

Devices

Device Hub

Stream Processing

Data Management, Storage, and Messaging

Advanced Analytics

Microservices and API Gateway

Visualization, Alerts, and Notifications

Worker Health and Safety: A Reference Implementation

Backstory

Solution Architecture

Downloading the Repository

Summary

Chapter 2: DevOps Using PowerShell, ARM, and VSTS

People

Process

Infrastructure as Code

Continuous Integration

Continuous Delivery

Tools

DevOps and Azure

PowerShell

Script Constructs

Azure PowerShell

Invoking Azure Cmdlets

Azure Resource Manager

ARM Templates

Part 1. $schema

Part 2. Content Version

Part 3. Parameters

Part 4. Variables

Part 5. Resources

Part 6. Outputs

Visual Studio Team Services

Summary

Chapter 3: Device Management Using IoT Hub

The Device Management Lifecycle

Planning

Provisioning

Azure IoT Hub

The Device API and the Device Manifest

Configuring and Monitoring

Device Twin

Tags

Desired and Reported Properties

Direct Methods

Queries

Jobs

Retiring

Summary

Chapter 4: Sensors, Devices, and Gateways

Sensors

Programmable Logic Controllers

Devices

GSM Modems

Protocol Gateway

GSM Modems and SMS

RFID

Bluetooth Beacons

Get Smart

Single-Board Computers

Microcontroller Software

Edge Gateways

Summary

Chapter 5: Real-Time Processing Using Azure Stream Analytics

The Lambda Architecture

What Is Streaming Analytics?

Real-Time Analytics

Streaming Implementations and Time-Series Analysis

Predicting Outcomes for Competitive Advantage

Stream Processing: Implementation Options in Azure

Choosing a Managed Streaming Analytics Engine in Azure

Streaming Technology Choice: Decision Considerations

Pain Points with Other Streaming Solutions

Reference Implementation Choice: Azure Streaming Analytics

Advantages of Azure Streaming Analytics

No Challenges with Deployment

Mission Critical Reliability

Business Continuity

No Challenges with Scale:

Low Startup Costs

Rapid Development

Development and Debugging Experience Through Azure Portal

Scheduling and Monitoring Built-In

Why Are Customers Using Azure Stream Analytics?

Key Vertical Scenarios to Explore for Azure Stream Analytics

Our Solution: Leveraging Azure Streaming Analytics

Streaming Analytics Jobs: INPUT definitions

Streaming Analytics Jobs: OUTPUT Definitions

Planning Streaming Analytics Outputs

Hot Path

Warm Path

Cold Path

Power BI for Real-Time Visualizations

Streaming Analytics Jobs: Data Transformations via SQL Queries

Azure Streaming Analytics SQL: Developer Friendly

Azure Streaming Analytics (ASA): SQL Query Dialect Features

SQL Query Language

Supported Data Types

Data Type Conversions

CAST

TRY_CAST

Temporal Semantic Functionality

Built-In Operators and Functions

User Defined Functions: Azure Machine Learning Integration

Event Delivery Guarantees Provided in Azure Stream Analytics

Exactly Once Delivery

Duplicate Records

Time Management Functions

The Importance of the TIMESTAMP BY Clause

Azure Stream Analytics: Unified Programming Model

Azure Stream Analytics: Examples of the SQL Programming Model

The Simplest Example

Tumbling Windows: A 10-Second Tumbling Window

Hopping Windows: A 10-Second Hopping Window with a 5-Second “Hop”

Sliding Windows: A 10-Second Sliding Window

Joining Multiple Streams

Detecting the Absence of Events

The Reference Implementation

Business Use Case Scenario

Summary

Chapter 6: Batch Processing with Data Factory and Data Lake Store

Azure Data Factory Overview

Pipelines and Activities

Activities

Linked Services

Datasets

Pipelines

Scheduling and Execution

Pipeline Copy Activity End-to-End Scenario

Scenario Prerequisites

JSON Definition

Monitoring and Managing Data Factory Pipelines

Data Factory Activity and Performance Tuning

Parallel Copy

Cloud Data Movement Units (DMUs)

Azure Data Lake Store

Hadoop Access

Security Layers

ADLS Encryption Key Management

Implementing Data Factory and Data Lake Store in the Reference Implementation

Summary

Chapter 7: Advanced Analytics with Azure Data Lake Analytics

Azure Data Lake Analytics

Getting Started with Azure Data Lake Analytics

Create an ADLA Account

Sample Scripts: Create, Submit, and Monitor Jobs

Azure Data Lake Tools for Visual Studio

ADLA U-SQL Features and Benefits

Types of U-SQL User-Defined Operators

U-SQL Windowing Functions

Reporting Aggregation Functions

Ranking Functions

Analytical Functions

ADLA Federated Queries: Querying the Data Where It Lives

Federated Queries: Overview of Steps Required to Query External Tables

Combining Row Sets

Azure Portal Integration

Big Data Jobs: Simplified Management and Administration

U-SQL: Optimization Is Built-In

Implementing ADLA in the Reference Implementation

Reference Implementation Summary

Summary

Handles Virtually All Types of Data

Productive from Day One

No Limits to Scale

Enterprise Grade

Reference Implementation

Just Scratching the Surface

Chapter 8: Advanced Analytics Using Machine Learning and R

What Is Machine Learning?

Understanding Machine Learning

Brief History of Machine Learning

Industry Applications of Machine Learning

Horizontal Patterns Across Vertical Industries

Overview of Azure Machine Learning

The Traditional Data Science Landscape

Democratizing Machine Learning

Azure Machine Learning Studio

The Cortana Intelligence Gallery

Azure Machine Learning: EXPERIMENTS

Azure Machine Learning: EXPERIMENT Modules

The Azure Machine Learning Data Science Flow

Microsoft R Server Overview

Processing limitations of Open Source R

Enter Microsoft R Server

Extend Machine Learning Experiments with the R Language Module

R Tools for Visual Studio

Implementing Azure Machine Learning and R in the Reference Implementation

Business Case for Machine Learning

Reference Implementation: Assumptions

Choosing a Machine Learning Algorithm

Summary

Chapter 9: Data Visualizations, Alerts, and Notifications with Power BI

The Modern Reporting Landscape

Overview of Power BI

The Power BI Service

Power BI Desktop

Unlocking Data Analysis

The Role of Excel and Power BI

Support for R Visualizations

Microsoft R Open

Power BI Desktop: R Script Visualizations

Power BI Data Sources

Power BI Mobile

Power BI Embedded

Licensing Model for Microsoft Power BI Embedded

Power BI ReST APIs

Power BI Custom Visuals

Power BI Natural Language Query

Power BI Cortana Integration

Cloud Reporting Cost Architectures

Alerts and Notifications

Azure Event Hub

Event Publishers

Event Hub Partitions

Event Consumers and Consumer Groups

Throughput Units

Streaming Analytics: Output to Event Hub

Azure Functions

Input Bindings

External Bindings

Developer BYOL (Bring Your Own Language)

Cost Effective Scaling

DevOps Integration with Azure Functions

Scheduled Functions

Reference Implementation

Implementation Overview

Summary

Chapter 10: Security and Identity

Threat Modeling

Threat Modeling Zones and IoT

Local Zone

Device Zone

Cloud Gateway Zone

Cloud Services Zone

Security Protocols

Azure Security Center

Data Encryption

Key Management

Identity

Authentication and Authorization

Multi-Tenancy

Summary

Chapter 11: Epilogue

Index

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Tags:

Bob Familiar,Jeff Barnes,Business,Real Time,Azure IoT,Cortana Intelligence,Suite,Digital Transformation