Don't worry. Not everyone knows it...

This article talks about an end-to-end flow, wherein an email content having specific subject line will be read, email body would be analyzed using Azure Cognitive Services (Sentiment analysis), analysis results would be saved in Azure Table Storage and finally chart would be drawn in Excel. All these steps include no coding at all. You can watch out the complete recording of this flow on my YouTube channel named Shweta Lodha.

Today I'll be mentioning one of the useful functions of Azure Text Analytics - Sentiment Analysis. Azure text analytics is a cloud-based offering from Microsoft and it provides Natural Language Processing over raw text.  Use Case Described In this article, I will explain how to use customer-provided product reviews to understand the market insight and how one can take a call on manufacturing the products in the future. Here is the pictorial representation of this use case.   Here are the high-level steps of how we can achieve this entire flow: Step 1 This entire process starts with the data collection part and for this, I'm using a CSV file with customer-provided reviews. Here is the gist of it: Step 2 Once data is collected, we need to import the data and for that, I'm using Jupyter Notebook inside Visual Studio Code. Here is the Python code to read and extract data from CSV file: import csv feedbacks = [ ] counter = 0 with open ( 'Feedback.csv' ,