Skip to content

Leveraged YouTube's Data API v3 to scrape data from 10 YouTube Channels using Python. The fetched data is stored in a MySQL Database. Developed a Power BI Dashboard to visualize data.

Notifications You must be signed in to change notification settings

rohanyg/YouTube-Data-Analytics

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

14 Commits
 
 
 
 

Repository files navigation

YouTube-Data-Analytics

Leveraged YouTube's Data API v3 to scrape data from 10 YouTube Channels using Python. The fetched data is stored in a MySQL Database and performed exploratory data analysis using SQL. Developed a Power BI Dashboard to visualize data.

Table of Contents

Project Overview

  1. Aim of this project is to perform the analysis on the data scraped from the youtube.
  2. To Analyze channel and video metrics to evaluate reach and engagement levels before partnering with them for promotional activities.
  3. To identify popular video topics, keywords and tags to target specific audience segments effectively.
  4. To Compare multiple YouTube channels to identify right channel for marketing campaigns.
  5. Tools used in this project are Python, MySQL, SQL and Power BI.

Problem Statement

The EdTech startup is struggling with low course enrollments and wants to improve it by targeted advertisement via YouTube channels. Understanding the potential reach and engagement metrics of YouTube collaborators is crucial for effective promotional strategies. This empowers the EdTech company to boost course enrollment, thereby recovering invested revenue into bootcamps and courses.

Data Gathering

  • Data was scraped from youtube with help of YouTube's Data API v3 using Python. Data collected is appended to the mysql database.

Data Cleaning

  • Validated the data understanding datapoints and checking range of values in each and every columns.
  • Data was clean as it is fetched from the youtube.

Data Analysis

  • Performed Exploratory Data Analysis on Youtubers Data using SQL answering the many questions.
  • Analyzed channel and video metrics to evaluate reach and engagement levels.
  • identified the popular video topics, keywords and tags
  • Compared multiple YouTube channels and identified right channel for marketing campaigns.

Data Visualization:

  • Designed the Power BI dashboard the communicate the findings effectively .
  • Published this Dashboard to workspace in Power BI Service.

Live Power BI Dashboard : https://app.powerbi.com/groups/me/reports/92a337b9-9d70-4512-bad5-f36e80ba12ec/ReportSection?experience=power-bi

Act

  • Suggested the potential youtube collabarator with good engagement for promotional activities.

About

Leveraged YouTube's Data API v3 to scrape data from 10 YouTube Channels using Python. The fetched data is stored in a MySQL Database. Developed a Power BI Dashboard to visualize data.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages