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Tanu272004/ReadMe.ReadMe
Tanmay Sharma – Professional Certification Portfolio
Welcome to my professional certification portfolio. This README highlights my continuous learning efforts and industry-relevant skills demonstrated through multiple certified courses and workshops, strengthening my data analytics, cloud computing, AI, and business intelligence expertise.

About
Certified Data Analyst skilled in Power BI, Excel, AWS, and AI tools—focused on delivering high-impact business insights and cloud-based analytical solutions.

Core Skills & Certifications
Power BI: Advanced dashboards, DAX, data modeling, business intelligence

Excel: Data cleaning, analysis, pivot tables, automation

AWS (Cloud): Practitioner Essentials, cost management, basic cloud architecture

AI & Automation: Generative AI planning, ChatGPT for analytics, workflow automation

Collaboration: GitHub version control, project teamwork

Professional Experience
Completed 45-day internship in real-world analytics projects

Developed and deployed multiple data-driven dashboards and reports

Why Choose This Portfolio?
Proven, hands-on skills matching MAANG-level data analytics expectations

Certifications and projects aligned with current industry demand

Strong focus on analytics, cloud, and data-driven decision making

Explore Projects
Visit repositories for case studies in retail analytics, financial modeling, and operational analysis

Each project includes installation steps and usage instructions
Next Steps
Seeking research, internship, or advanced analyst roles. 
Contact via LinkedIn or see full project details on GitHub.

GitHub: https://github.com/Tanu272004
LinkedIn: https://www.linkedin.com/in/tanmay-sharma-800599373/
Portfolio-Link:https://tinyurl.com/Azure2724
Website-Link:  https://tinyurl.com/Insights2427
Wordpress-Link: http://tanmayportfolio52.wordpress.com
Research-Paper-Link: https://doi.org/10.6084/m9.figshare.29991352.v1
Blob_Post-Link: https://hashnode.com/@tanmay27
Certifications-Link: https://drive.google.com/file/d/1V31C-xYD1pQleMeEmrxzFpMPbvSYVrA5/view?usp=sharing
Microsoft_Achievements-Link: https://learn.microsoft.com/en-us/users/tanmaysharma-3825/achievements
Internship portolio website Link Canva: https://tanmay2427-portfolio.my.canva.site/prodigy-infotech-data-science-internship/
Resume: https://drive.google.com/file/d/1Ma2xQy_dDA5ZWQw0_9YTAeE0QSLj6gef/view?usp=sharing

Thank you for taking the time to review my certification journey and professional preparation. I am excited to continue growing as a data and AI Analyst.















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  1. Netflix_analysis_bi_project Netflix_analysis_bi_project Public

    End-to-end Netflix BI Project using Python, Azurite, MySQL, and Power BI. Includes data engineering workflows, dynamic dashboards, and cloud storage simulation.

    Python

  2. Amazon_Analysis_Project Amazon_Analysis_Project Public

    Short Description: An end-to-end Amazon Sales Analytics project demonstrating data engineering, SQL analytics, BI dashboards, cloud integration, and predictive modeling.

    Python

  3. Amazon_CLV_Analytics_Project Amazon_CLV_Analytics_Project Public

    Amazon Customer Lifetime Value (CLV) Analysis This project demonstrates an end-to-end analytics workflow for analyzing Customer Lifetime Value (CLV) using: Python – MySQL. Power BI . Azure (Azurite)

    Python 1

  4. Amazon_Sentiments Amazon_Sentiments Public

    "End-to-end sentiment analysis pipeline for Amazon reviews leveraging Python (TextBlob), MySQL, and Power BI with cloud-ready architecture (Azure Blob Storage simulation)."

    Python

  5. Netflix_Content_Recommendation Netflix_Content_Recommendation Public

    ChatGPT said: Here’s a short and professional GitHub description for your Netflix project: 📽️ Netflix Content Recommendation System & Ratings Dashboard A complete end-to-end data analytics and mach…

    Python 1

  6. Tesla_Stock_Analysis Tesla_Stock_Analysis Public

    Project Description: This project analyzes Tesla’s financial growth and stock performance from 2015 to 2024 using simulated real-world data. Python was used to generate and clean the dataset, while…

    Python