Section 1: Problem Statement

2.1 The Data Processing Challenge

A company has a large amount of data that is generated by various sources, such as IoT devices, social media, and e-commerce websites. They want to build a platform that can process and analyse this data in real-time, in order to gain insights and make data-driven decisions. However, they do not want to have to manage the underlying infrastructure, as they want to focus on developing and improving the data processing and analytics logic.

Azure Functions and Azure Blob Storage: Building Scalable Serverless Applications

Serverless computing is a cloud computing execution model in which the cloud provider dynamically allocates resources to run an application’s code, and the user only pays for the time that the code is actually running. This allows developers to focus on building and deploying their applications, without having to worry about the underlying infrastructure. One example of using server-less on Microsoft Azure is to build a real-time data processing and analytics platform.

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Section 1: Problem Statement

2.1 The Data Processing Challenge...

Section 3: Solution/Architecture

3.1 Leveraging Azure for Serverless Data Processing...

Section 4: Technical Details and Implementation

4.1 Step-by-Step Implementation...

Section 5: Challenges in Implementing the Solution

5.1 Learning Curve...

Section 6: Business Benefits

6.1 Focusing on Core Competencies...

Conclusion

Overall, using serverless on Azure to build a real-time data processing and analytics platform can provide significant business value by allowing the company to gain insights from their data more quickly and make data-driven decisions more effectively....

FAQs On Azure Functions and Azure Blob Storage

1. What Are The Benefits Of Using Serverless Computing On Azure?...