Azure Stream Analytics – End-to-End Analytics Solutions!
Azure Stream Analytics – End-to-End Analytics Solutions!, available at $44.99, has an average rating of 3.25, with 39 lectures, 1 quizzes, based on 19 reviews, and has 167 subscribers.
You will learn about Develop real-time event processing with Azure streaming. Integrate BI and enhance features in Azure Stream Analytics. Design and manage Stream Analytics jobs. Build end to end social media analytics solutions with Azure Stream Analytics. Build end-to-end real-time IoT solutions using Azure Stream Analytics. Implement real-time fraud detection using Azure Stream Analytics with Cortana This course is ideal for individuals who are Big data developers, data analysts, data scientists, and Azure developers who are looking to get familiar with Microsoft’s Azure Stream Analytics and want to develop a real-time event processing solutions! It is particularly useful for Big data developers, data analysts, data scientists, and Azure developers who are looking to get familiar with Microsoft’s Azure Stream Analytics and want to develop a real-time event processing solutions!.
Enroll now: Azure Stream Analytics – End-to-End Analytics Solutions!
Summary
Title: Azure Stream Analytics – End-to-End Analytics Solutions!
Price: $44.99
Average Rating: 3.25
Number of Lectures: 39
Number of Quizzes: 1
Number of Published Lectures: 39
Number of Published Quizzes: 1
Number of Curriculum Items: 40
Number of Published Curriculum Objects: 40
Original Price: $199.99
Quality Status: approved
Status: Live
What You Will Learn
- Develop real-time event processing with Azure streaming.
- Integrate BI and enhance features in Azure Stream Analytics.
- Design and manage Stream Analytics jobs.
- Build end to end social media analytics solutions with Azure Stream Analytics.
- Build end-to-end real-time IoT solutions using Azure Stream Analytics.
- Implement real-time fraud detection using Azure Stream Analytics with Cortana
Who Should Attend
- Big data developers, data analysts, data scientists, and Azure developers who are looking to get familiar with Microsoft’s Azure Stream Analytics and want to develop a real-time event processing solutions!
Target Audiences
- Big data developers, data analysts, data scientists, and Azure developers who are looking to get familiar with Microsoft’s Azure Stream Analytics and want to develop a real-time event processing solutions!
Microsoft Azure is a very popular cloud computing service used by many organizations around the world. Its latest analytics offering: Stream Analytics – allows you to process and acquire actionable insights from different kinds of data in real-time. If you are an analytics professional looking to get familiar with Microsoft’s Azure stream analytics, then this Course is perfect for you!
This comprehensive 2-in-1 course is concise and appropriate for evaluating deep aspects of building real-world data-centric and data processing with the Azure Data Platform! You’ll begin with implementing Azure’s simple, declarative model to build real-time data transformations for processing IoT streams, real-time data analysis, and more! Understand the development aspects of Azure Stream analytics to build real-time event processing solutions. Finally, you’ll build end-to-end analytics solutions with Azure Stream Analysis!
By the end of the course, you’ll understand the development aspects of Azure Stream analytics to build end-to-end, real-time event processing solutions!
Contents and Overview
This training program includes 2 complete courses, carefully chosen to give you the most comprehensive training possible.
The first course, Real-time Data Processing with Azure Stream Analytics, covers real-time data processing with Azure Stream Analytics. This video is your guide to understanding the basics of how Azure Stream Analytics works, and then building your own analytics solution using its capabilities. You will start by learning what stream analytics is, and why it is a popular choice for acquiring real-time insights from data. Then you will be introduced to Azure Stream Analytics, and learn how you can use the tools and functions in Azure to develop your own Streaming Analytics. During the course of the video, you will build streaming solutions for the IoT, fraud detection, real-time event processing, and more. The video also shows you how you can manage, monitor, and scale your solution for optimal performance. By the end of this tutorial, you will have mastered using Azure Stream Analytics to develop an efficient analytics solution that can work with any type of data.
The second course, Managing and Monitoring Streaming Solutions in Azure, covers the development aspects of Azure Stream analytics to build real-time event processing solutions. This course will give you a good understanding of the development aspects of Azure Stream analytics to build real-time event processing solutions. The course mainly focuses on monitoring scaling aspects to increase throughput in your streaming jobs and supplies a varied troubleshooting guide for big data developers/architects. The course provides end-to-end demonstrations for solutions to real-world business problems related to Internet of Things and fraud detection scenarios with the help of Microsoft Cortana Intelligence Gallery.
By the end of the course, you’ll understand the development aspects of Azure Stream analytics to build end-to-end, real-time event processing solutions!
About the Authors
● Anindita Basakis working as Big Data & Cloud Architect for one of Computer Software giant & working with Microsoft Azure for last 8+ years. She has worked with various teams of Microsoft as FTE in the role of Azure Development Support Engineer, Pro-Direct Delivery Manager, and Partner Technical Consultant. She has been technical reviewer for five books from Packt Publisher on Azure HDInsight, SQL Server Business Intelligence, and Hadoop Development & Smart Learning with Internet of Things & Decision Science. Recently, she authored two video courses on Azure Stream Analytics from Packt Publishing.
Course Curriculum
Chapter 1: Real-time Data Processing with Azure Stream Analytics
Lecture 1: The Course Overview
Lecture 2: Real-time Data Processing with Azure
Lecture 3: Introduction to Azure Stream Analytics
Lecture 4: Integration of Big Data Lambda Architecture with Interactive Data Analysis
Lecture 5: Exploring Apache Storm and Azure Streaming Analysis
Lecture 6: Tools for Visual Studio for Creation of Azure Stream Analytics job
Lecture 7: Creating Azure Stream Analytics Job Using Azure Portal
Lecture 8: Developing Azure Stream Analytics Job Using Azure Resource Manager Template
Lecture 9: Development of Streaming Job with Various Data Input and Output
Lecture 10: Lap Around Stream Analytics – TSQL Language Reference
Lecture 11: Learning Common Query Patterns in Streaming Analytics-TSQL
Lecture 12: Process Streaming Data Through Azure Stream Analytics with Power BI
Lecture 13: Application of Windowing Functions with Streaming Solution in Azure
Lecture 14: Utilizing Reference Data with Streaming Analytics
Lecture 15: Implementing Output of Stream Analytics to Azure Data Lake Store
Lecture 16: Connecting Output of Stream Analytics with Azure Functions
Lecture 17: JavaScript UDF Integration with Azure Stream Analytics -TSQL
Lecture 18: Utilizing Azure Machine Learning Integrated with Stream Analytics
Lecture 19: Application of .NET Management SDK with Streaming Solution in Azure
Chapter 2: Managing and Monitoring Streaming Solutions in Azure
Lecture 1: The Course Overview
Lecture 2: Stream Analytics Jobs Reliability
Lecture 3: Monitoring Jobs Programmatically
Lecture 4: Scaling a Stream Analytics Job to Increase Throughput
Lecture 5: Troubleshooting ASA Jobs
Lecture 6: Monitor ASA Jobs Through Azure Portal
Lecture 7: Testing Queries in Azure Streaming Analytics
Lecture 8: Debugging of Jobs Using 'SELECT INTO' Clause
Lecture 9: Azure Service Bus Event Order Handling
Lecture 10: Optimizing Streaming Units
Lecture 11: Operationalize Stream Analytics Job Diagnostic Logs
Lecture 12: Social Media Sentiment Analysis in Real-Time with Solution Architecture
Lecture 13: Configuration of Stream Analytics Jobs
Lecture 14: Visualize Output for Social Media Sentiment Analysis
Lecture 15: Real-Time Traffic Analysis in IoT Scenario with Solution Architecture
Lecture 16: Setting up Environment for Real-Time IoT Solution
Lecture 17: Testing of Streaming Analytics Queries for Real-Time IoT Solution
Lecture 18: Real-World Fraud Detection Analytics with Azure Streaming Analytics
Lecture 19: Provision of Azure Stream Analytics Job and its Input Connector
Lecture 20: Start of ASA job for Real-Time Event Processing and View Output
Instructors
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Packt Publishing
Tech Knowledge in Motion
Rating Distribution
- 1 stars: 5 votes
- 2 stars: 2 votes
- 3 stars: 4 votes
- 4 stars: 2 votes
- 5 stars: 6 votes
Frequently Asked Questions
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