Implement Real Time Analytics using Azure Stream Analytics from Coursera

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

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Know what's good

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Examines real-time data processing, which is highly relevant in industry

Taught by Amit Navgire, who is recognized for their work in data processing

Develops skills in using Azure Stream Analytics for real-time analytics, which is a core skill for data engineers

Provides hands-on labs and interactive materials for experiential learning

Requires an Azure subscription account with owner level access, which may be a barrier for some learners

Reviews summary

Complex user interface

**1 review** The most common feedback is that the user interface is difficult to comprehend and seems to be missing important information.

Not enough documentation

"Please explain completely, users don't want to follow instructions "blindly" as described."

Frustrating user interface

"Poorly compiled and articulated."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Implement Real Time Analytics using Azure Stream Analytics with these activities:

Revise Stream Processing Concepts

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Recall the fundamental principles of stream processing to deepen your understanding.

Browse courses on Stream Processing

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Review the concepts of real-time vs. batch processing
Explore different stream processing architectures (lambda, kappa)
Refresh your knowledge on data streaming techniques

Review Cloud Computing Concepts

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Strengthen your foundational knowledge of cloud computing to better grasp Azure concepts.

Browse courses on Azure

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Revisit basic cloud concepts (IaaS, PaaS, SaaS)
Explore different cloud platforms and their offerings
Review Azure-specific services and their applications

Follow Azure Stream Analytics Tutorials

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Supplement your learning with interactive, step-by-step tutorials to reinforce concepts.

Browse courses on Azure Stream Analytics

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Follow Microsoft's official Azure Stream Analytics tutorials
Explore other online tutorials and resources
Practice applying the concepts learned in the tutorials

Two other activities

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Practice SQL Queries

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Enhance your understanding of SQL syntax and data manipulation techniques.

Browse courses on Azure Stream Analytics

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Review basic SQL concepts (SELECT, WHERE, JOIN)
Practice writing queries to filter, aggregate, and transform data
Use online resources or tutorials for additional practice

Build a Personal Analytics Dashboard

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Apply your skills to create a practical tool for data analysis and visualization.

Browse courses on Data Visualization

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Identify a relevant dataset or API
Design the dashboard layout and visualizations
Implement the dashboard using Azure Stream Analytics and Power BI
Deploy and share the dashboard with others

Career center

Learners who complete Implement Real Time Analytics using Azure Stream Analytics will develop knowledge and skills that may be useful to these careers:

Data Analyst

Data Analysts play a critical role by using their statistical and analytical skills to transform raw data into valuable insights. This course provides a solid foundation for Data Analysts, as it covers the fundamentals of real-time data processing and analytics using Azure Stream Analytics. By understanding how to process and analyze streaming data, Data Analysts can uncover hidden patterns and trends, gaining actionable insights to drive better decision-making.

See salaries and explore the career path for Data Analyst

Data Engineer

Data Engineers design and build the infrastructure that supports data processing and analytics. This course provides Data Engineers with hands-on experience in setting up and configuring Azure Stream Analytics, a powerful tool for real-time data processing. By learning how to integrate Azure Stream Analytics with other Azure services, Data Engineers can create scalable and reliable data pipelines.

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Machine Learning Engineer

Machine Learning Engineers build and deploy machine learning models to solve complex problems. This course may help Machine Learning Engineers by providing a foundation in real-time data processing and analytics. By understanding how to process and analyze streaming data, Machine Learning Engineers can develop models that can adapt to changing data patterns and make predictions in real time.

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Software Engineer

Software Engineers design, develop, and maintain software systems. This course may help Software Engineers by providing a foundation in real-time data processing and analytics. By understanding how to process and analyze streaming data, Software Engineers can build applications that can respond to real-time events and changes in data.

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Cloud Architect

Cloud Architects design and manage cloud computing infrastructure. This course may help Cloud Architects by providing a foundation in real-time data processing and analytics. By understanding how to process and analyze streaming data, Cloud Architects can design and implement cloud-based solutions that can handle real-time data workloads.

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Data Scientist

Data Scientists use data to solve complex problems and make predictions. This course may help Data Scientists by providing a foundation in real-time data processing and analytics. By understanding how to process and analyze streaming data, Data Scientists can develop models and algorithms that can make predictions in real time.

See salaries and explore the career path for Data Scientist

Business Analyst

Business Analysts use data to understand business needs and develop solutions. This course may help Business Analysts by providing a foundation in real-time data processing and analytics. By understanding how to process and analyze streaming data, Business Analysts can gain insights into real-time business trends and make recommendations to improve operations.

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Product Manager

Product Managers are responsible for the development and management of products. This course may help Product Managers by providing a foundation in real-time data processing and analytics. By understanding how to process and analyze streaming data, Product Managers can gain insights into real-time usage and customer feedback, which can help them make better decisions about product development and marketing.

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Marketing Analyst

Marketing Analysts use data to understand marketing campaigns and customer behavior. This course may help Marketing Analysts by providing a foundation in real-time data processing and analytics. By understanding how to process and analyze streaming data, Marketing Analysts can gain insights into real-time marketing performance and customer engagement, which can help them optimize campaigns and improve results.

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Sales Analyst

Sales Analysts use data to understand sales performance and identify opportunities. This course may help Sales Analysts by providing a foundation in real-time data processing and analytics. By understanding how to process and analyze streaming data, Sales Analysts can gain insights into real-time sales trends and customer behavior, which can help them identify new leads and close deals faster.

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Financial Analyst

Financial Analysts use data to understand financial markets and make investment decisions. This course may help Financial Analysts by providing a foundation in real-time data processing and analytics. By understanding how to process and analyze streaming data, Financial Analysts can gain insights into real-time market trends and make more informed investment decisions.

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Risk Analyst

Risk Analysts use data to identify and manage risks. This course may help Risk Analysts by providing a foundation in real-time data processing and analytics. By understanding how to process and analyze streaming data, Risk Analysts can gain insights into real-time risk events and take steps to mitigate potential losses.

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Operations Analyst

Operations Analysts use data to improve operational efficiency and effectiveness. This course may help Operations Analysts by providing a foundation in real-time data processing and analytics. By understanding how to process and analyze streaming data, Operations Analysts can gain insights into real-time operational performance and identify areas for improvement.

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