Rahul Bhadauria

Data enthusiast with knowledge in Python, SQL, Tableau, and Excel. Exhibiting both leadership and collaboration skills while possessing excellent written and verbal communication skills. Striving to establish a successful career as a Data Analyst by utilizing skills to provide valuable insights, innovative solutions and problem solving.

HR attrition data 

Problem: Worked on a company's attrition data to help find out the trends and generalize the attrition.
Tools used: Python (for data cleaning and taking insights), SQL (To generate some meaningful insights), Power
BI (for creating the schema, data visualization and Dashboard).
Analyzed the data to help find some meaningful insights into attrition and its relation with gender, experience,
job profile, qualification, distance from home, marriage status, age, job satisfaction etc.
Created an interactive dashboard to showcase all the insights in the form of Data Visualization.

Ecommerce dashboard 

Problem: To create and draw meaningful insights from ecom data that can help company increase the revenue and leverage its strength in selling.
Tools used: (Excel and SQL- Used power query and pivot table to generate the meaningful insights and
created a dashboard)

Analyzed the data to find out some helpful insights related directly to higher revenue generation that can be presented as strength of the company. Checked various patterns of customer while making purchase like the average gap between two consecutive purchase, payment method that is more frequently, which shipper contributed in higher revenue generation, list of high demanding products, preferred brands etc.

Created an interactive dashboard to showcase all the insights in the form of Data Visualization.

Instahyre Website Analyses 

Problem: To create a website/search portal for candidates to see the number of job openings with location, name of company and position on the basis of their skills. All the jobs related to their skills will be consolidated at one place.
Tools used: Python (for web scraping, data cleaning, using NLTK library, Class formation on clusters, flask
library for creating the website), SQL (for generating the insights and the database), HTML and CSS (for
creating the website).
Analyzed the data to see the latest trend in the market in terms of job skills, locations, a company that has the
highest number of hiring and its linked followers with HR details, job title.