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In this project, we are going to see how to "Implement Real Time Analytics using Azure Stream Analytics"
Data processing is broadly categorized into two main categories: Batch processing & Real time processing.
We are going to focus on real time data processing and Azure Stream Analytics is a popular service which is used to process and perform analytics on real time data stream.
Hence , in this project we are going to see with an example how to implement a solution using Azure Stream Analytics and process real time stream of data.
Pre requisites:
1. Azure subscription account(its preferred to have owner level access on the subscription account)
Here is a brief description of the tasks we are going to perform in this project:
Task1: Understand the Project Scenario
In this task, we are going to see an overview of the project to be implemented and also the different components involved in this project and how they are linked to each other
Task2: Setup the project environment
In this task, we are going to create Azure Event Hub, Azure SQL Database, download and install Real Time Data Generator App.
Task3: Configure the different components created in previous task
In this task, we are going to connect the live data generator app with the event hub and also create the output and reference tables in Azure SQL Database
Task4: Configure Azure Stream Analytics Job
In this task, we are going to configure the input, reference input and output in Azure Stream Analytics Job
Task5: Configure Query in Stream Analytics job
In this task, we are going to write the query in Stream Analytics job which is used to process, analyze and transform the source data which will be received from event hub.
Also, we will run the Stream Analytics job to see a demo of how it processes the input data from event hub and loads the data in output table in SQL database.
Task6: Configure reference input in Stream Analytics job
In this task, we are going to see how to use the reference input in the query of Azure Stream Analytics job.
Also, we will run the Stream Analytics job to see a demo of how it processes reference input and loads data in output table in SQL database
Data processing is broadly categorized into two main categories: Batch processing & Real time processing.
We are going to focus on real time data processing and Azure Stream Analytics is a popular service which is used to process and perform analytics on real time data stream.
Hence , in this project we are going to see with an example how to implement a solution using Azure Stream Analytics and process real time stream of data.
Pre requisites:
1. Azure subscription account(its preferred to have owner level access on the subscription account)
Here is a brief description of the tasks we are going to perform in this project:
Task1: Understand the Project Scenario
In this task, we are going to see an overview of the project to be implemented and also the different components involved in this project and how they are linked to each other
Task2: Setup the project environment
In this task, we are going to create Azure Event Hub, Azure SQL Database, download and install Real Time Data Generator App.
Task3: Configure the different components created in previous task
In this task, we are going to connect the live data generator app with the event hub and also create the output and reference tables in Azure SQL Database
Task4: Configure Azure Stream Analytics Job
In this task, we are going to configure the input, reference input and output in Azure Stream Analytics Job
Task5: Configure Query in Stream Analytics job
In this task, we are going to write the query in Stream Analytics job which is used to process, analyze and transform the source data which will be received from event hub.
Also, we will run the Stream Analytics job to see a demo of how it processes the input data from event hub and loads the data in output table in SQL database.
Task6: Configure reference input in Stream Analytics job
In this task, we are going to see how to use the reference input in the query of Azure Stream Analytics job.
Also, we will run the Stream Analytics job to see a demo of how it processes reference input and loads data in output table in SQL database
