Skip to content
View SurajGusain0007's full-sized avatar
๐Ÿ’ญ
stay positive like a proton
๐Ÿ’ญ
stay positive like a proton

Block or report SurajGusain0007

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Please don't include any personal information such as legal names or email addresses. Maximum 100 characters, markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this userโ€™s behavior. Learn more about reporting abuse.

Report abuse
SurajGusain0007/README.md

Welcome to My GitHub Profile! ๐Ÿ‘‹

Hello there! I'm Suraj Gusain, a passionate data enthusiast and recent B.Tech graduate (Class of 2021) with a strong foundation in computer science and data analysis. I am thrilled to share my journey, skills, and projects with you.

Academic Achievements ๐ŸŽ“

  • Bachelor of Technology (B.Tech) in Computer Science and Engineering, Kurushetra University, 2021
  • CGPA: 8.4/10.0
  • I attempted the GATE exam in 2022 in the field of Computer Science and Engineering to enhance my knowledge and skills. Although I did not qualify, this experience has motivated me to further strengthen my
    expertise in this area. Through continuous learning and hands-on projects, I am committed to advancing my knowledge and contributing meaningfully to the world of data analysis and technology.

Courses & Certifications ๐Ÿ“š

  • Data Analyst Certification, 6-Month Course, Skilledge, May 2022-Nov 2022
  • HackerRank Basic Assessment Test, Completed with Distinction, May 2022
  • HackerRank Intermediate Assessment Test, Completed with Distinction, Auguest 2022
  • Meriskill Virtual Internship Completion, July 2023 -Sep2023

Skills & Technologies ๐Ÿ’ป

  • Programming Languages: Python, SQL,
  • Data Analysis Tools: Pandas, NumPy, Matplotlib, Seaborn
  • Databases: MySQL, SQLite
  • Tools: Jupyter Notebook, Git, GitHub,Mysql Workbench,Google collab
  • Others: Data Cleaning, Data Visualization, Statistical Analysis
  • Data Visualization Tools: Excel,Power Bi,Power Query,Dax,Data Modelling
  • Iโ€™m currently learning Machine Learning

Projects Portfolio ๐Ÿš€

IPL-PROJECT-WEBSITE

FAASO_SQL_ANALYSIS_PROJECT

ZOMATO_EDA_WITH_PYTHON_AND_SQL

Netflix-EDA-Project

Power BI PROJECTS ๐Ÿš€

๐—ฃ๐—ฟ๐—ผ๐—ฏ๐—น๐—ฒ๐—บ ๐—ฆ๐˜๐—ฎ๐˜๐—ฒ๐—บ๐—ฒ๐—ป๐˜: ๐—”๐˜๐—น๐—ถ๐—ค ๐— ๐—ฎ๐—ฟ๐˜ ๐—ฐ๐˜‚๐—ฟ๐—ฟ๐—ฒ๐—ป๐˜๐—น๐˜† ๐—ณ๐—ฎ๐—ฐ๐—ฒ๐˜€ ๐—ฎ ๐—ฝ๐—ฟ๐—ผ๐—ฏ๐—น๐—ฒ๐—บ ๐˜„๐—ต๐—ฒ๐—ฟ๐—ฒ ๐—ฎ ๐—ณ๐—ฒ๐˜„ ๐—ธ๐—ฒ๐˜† ๐—ฐ๐˜‚๐˜€๐˜๐—ผ๐—บ๐—ฒ๐—ฟ๐˜€ ๐—ฑ๐—ถ๐—ฑ ๐—ป๐—ผ๐˜ ๐—ฟ๐—ฒ๐—ฐ๐—ฒ๐—ถ๐˜ƒ๐—ฒ ๐˜๐—ต๐—ฒ๐—ถ๐—ฟ ๐—ฎ๐—ป๐—ป๐˜‚๐—ฎ๐—น ๐—ฐ๐—ผ๐—ป๐˜๐—ฟ๐—ฎ๐—ฐ๐˜๐˜€ ๐—ฑ๐˜‚๐—ฒ ๐˜๐—ผ ๐—ถ๐˜€๐˜€๐˜‚๐—ฒ๐˜€ ๐—ถ๐—ป ๐—ณ๐˜‚๐—น๐—น ๐—ผ๐˜ƒ๐—ฒ๐—ฟ ๐—ฎ ๐—ฐ๐—ผ๐—ป๐˜๐—ฟ๐—ฎ๐—ฐ๐˜๐—ฒ๐—ฑ ๐—ฝ๐—ฒ๐—ฟ๐—ถ๐—ผ๐—ฑ, ๐˜„๐—ต๐—ถ๐—ฐ๐—ต ๐—ฐ๐—ผ๐˜‚๐—น๐—ฑ ๐—ต๐—ฎ๐—ฟ๐—บ ๐—ฐ๐˜‚๐˜€๐˜๐—ผ๐—บ๐—ฒ๐—ฟ ๐˜€๐—ฎ๐˜๐—ถ๐˜€๐—ณ๐—ฎ๐—ฐ๐˜๐—ถ๐—ผ๐—ป ๐—ฎ๐—ป๐—ฑ ๐—ผ๐˜ƒ๐—ฒ๐—ฟ๐—ฎ๐—น๐—น ๐—ฏ๐˜‚๐˜€๐—ถ๐—ป๐—ฒ๐˜€๐˜€ ๐—ฝ๐—ฒ๐—ฟ๐—ณ๐—ผ๐—ฟ๐—บ๐—ฎ๐—ป๐—ฐ๐—ฒ. ๐— ๐—ฎ๐—ป๐—ฎ๐—ด๐—ฒ๐—บ๐—ฒ๐—ป๐˜ ๐˜„๐—ฎ๐—ป๐˜๐˜€ ๐˜๐—ผ ๐—ฎ๐—ฑ๐—ฑ๐—ฟ๐—ฒ๐˜€๐˜€ ๐˜๐—ต๐—ถ๐˜€ ๐—ถ๐˜€๐˜€๐˜‚๐—ฒ ๐—ฏ๐—ฒ๐—ณ๐—ผ๐—ฟ๐—ฒ ๐—ฒ๐˜…๐—ฝ๐—ฎ๐—ป๐—ฑ๐—ถ๐—ป๐—ด ๐˜๐—ผ ๐—ผ๐˜๐—ต๐—ฒ๐—ฟ ๐—ฐ๐—ถ๐˜๐—ถ๐—ฒ๐˜€ ๐—ฎ๐—ป๐—ฑ ๐—ถ๐˜€ ๐˜€๐—ฒ๐—ฒ๐—ธ๐—ถ๐—ป๐—ด ๐—ฎ ๐˜€๐—ผ๐—น๐˜‚๐˜๐—ถ๐—ผ๐—ป ๐˜๐—ผ ๐˜๐—ฟ๐—ฎ๐—ฐ๐—ธ ๐˜๐—ต๐—ฒ '๐—ข๐—ป ๐˜๐—ถ๐—บ๐—ฒ' ๐—ฎ๐—ป๐—ฑ '๐—œ๐—ป ๐—™๐˜‚๐—น๐—น' ๐—ฑ๐—ฒ๐—น๐—ถ๐˜ƒ๐—ฒ๐—ฟ๐˜† ๐˜€๐—ฒ๐—ฟ๐˜ƒ๐—ถ๐—ฐ๐—ฒ ๐—น๐—ฒ๐˜ƒ๐—ฒ๐—น๐˜€ ๐—ณ๐—ผ๐—ฟ ๐—ฎ๐—น๐—น ๐—ฐ๐˜‚๐˜€๐˜๐—ผ๐—บ๐—ฒ๐—ฟ๐˜€ ๐—ฑ๐—ฎ๐—ถ๐—น๐˜† ๐˜๐—ผ ๐—ฒ๐—ป๐˜€๐˜‚๐—ฟ๐—ฒ ๐—ฐ๐˜‚๐˜€๐˜๐—ผ๐—บ๐—ฒ๐—ฟ ๐˜€๐—ฎ๐˜๐—ถ๐˜€๐—ณ๐—ฎ๐—ฐ๐˜๐—ถ๐—ผ๐—ป ๐—น๐—ฒ๐˜ƒ๐—ฒ๐—น๐˜€ ๐—ฎ๐—ฟ๐—ฒ ๐—บ๐—ฎ๐—ถ๐—ป๐˜๐—ฎ๐—ถ๐—ป๐—ฒ๐—ฑ ๐—ผ๐—ฟ ๐—ถ๐—บ๐—ฝ๐—ฟ๐—ผ๐˜ƒ๐—ฒ๐—ฑ."

๐Ÿ“Œ ๐—œ๐—ป ๐˜€๐˜‚๐—ฝ๐—ฝ๐—น๐˜† ๐—ฐ๐—ต๐—ฎ๐—ถ๐—ป ๐—ž๐—ฒ๐˜† ๐—ฃ๐—ฒ๐—ฟ๐—ณ๐—ผ๐—ฟ๐—บ๐—ฎ๐—ป๐—ฐ๐—ฒ ๐—œ๐—ป๐—ฑ๐—ถ๐—ฐ๐—ฎ๐˜๐—ผ๐—ฟ๐˜€ (๐—ž๐—ฃ๐—œ๐˜€), "๐—ข๐—ง%" ๐—ฐ๐—ฎ๐—ป ๐˜€๐˜๐—ฎ๐—ป๐—ฑ ๐—ณ๐—ผ๐—ฟ "๐—ข๐—ป-๐—ง๐—ถ๐—บ๐—ฒ ๐—ฃ๐—ฒ๐—ฟ๐—ฐ๐—ฒ๐—ป๐˜๐—ฎ๐—ด๐—ฒ." ๐—œ๐˜ ๐—บ๐—ฒ๐—ฎ๐˜€๐˜‚๐—ฟ๐—ฒ๐˜€ ๐˜๐—ต๐—ฒ ๐—ฝ๐—ฒ๐—ฟ๐—ฐ๐—ฒ๐—ป๐˜๐—ฎ๐—ด๐—ฒ ๐—ผ๐—ณ ๐—ผ๐—ฟ๐—ฑ๐—ฒ๐—ฟ๐˜€ ๐—ผ๐—ฟ ๐˜€๐—ต๐—ถ๐—ฝ๐—บ๐—ฒ๐—ป๐˜๐˜€ ๐˜๐—ต๐—ฎ๐˜ ๐—ฎ๐—ฟ๐—ฒ ๐—ฑ๐—ฒ๐—น๐—ถ๐˜ƒ๐—ฒ๐—ฟ๐—ฒ๐—ฑ ๐—ผ๐—ฟ ๐—ณ๐˜‚๐—น๐—ณ๐—ถ๐—น๐—น๐—ฒ๐—ฑ ๐—ผ๐—ป ๐˜๐—ถ๐—บ๐—ฒ ๐—ฎ๐˜€ ๐—ฝ๐—น๐—ฎ๐—ป๐—ป๐—ฒ๐—ฑ, ๐—ถ๐—ป๐—ฑ๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ป๐—ด ๐˜๐—ต๐—ฒ ๐—ฒ๐—ณ๐—ณ๐—ถ๐—ฐ๐—ถ๐—ฒ๐—ป๐—ฐ๐˜† ๐—ฎ๐—ป๐—ฑ ๐—ฟ๐—ฒ๐—น๐—ถ๐—ฎ๐—ฏ๐—ถ๐—น๐—ถ๐˜๐˜† ๐—ผ๐—ณ ๐—ฎ ๐˜€๐˜‚๐—ฝ๐—ฝ๐—น๐˜† ๐—ฐ๐—ต๐—ฎ๐—ถ๐—ป ๐—ผ๐—ฝ๐—ฒ๐—ฟ๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—ถ๐—ป ๐—บ๐—ฒ๐—ฒ๐˜๐—ถ๐—ป๐—ด ๐—ฑ๐—ฒ๐—น๐—ถ๐˜ƒ๐—ฒ๐—ฟ๐˜† ๐˜€๐—ฐ๐—ต๐—ฒ๐—ฑ๐˜‚๐—น๐—ฒ๐˜€.

๐Ÿ“Œ ๐—œ๐—™ %:๐˜๐—ต๐—ถ๐˜€ ๐—บ๐—ฒ๐—ฎ๐˜€๐˜‚๐—ฟ๐—ฒ ๐—ถ๐˜€ ๐—บ๐—ฒ๐—ฎ๐˜€๐˜‚๐—ฟ๐—ฒ๐—ฑ ๐—ฎ๐˜ ๐˜๐—ต๐—ฒ ๐—ผ๐—ฟ๐—ฑ๐—ฒ๐—ฟ ๐—น๐—ฒ๐˜ƒ๐—ฒ๐—น. ๐—œ๐˜ ๐—ฑ๐—ฒ๐˜๐—ฒ๐—ฟ๐—บ๐—ถ๐—ป๐—ฒ๐˜€ ๐—ถ๐—ณ ๐—ฎ๐—ป ๐—ผ๐—ฟ๐—ฑ๐—ฒ๐—ฟ ๐—ถ๐˜€ ๐—ฑ๐—ฒ๐—น๐—ถ๐˜ƒ๐—ฒ๐—ฟ๐—ฒ๐—ฑ ๐—ถ๐—ป ๐—ณ๐˜‚๐—น๐—น ๐—ฎ๐˜€ ๐—ฝ๐—ฒ๐—ฟ ๐˜๐—ต๐—ฒ ๐—ฟ๐—ฒ๐—พ๐˜‚๐—ฒ๐˜€๐˜๐—ฒ๐—ฑ ๐—พ๐˜‚๐—ฎ๐—ป๐˜๐—ถ๐˜๐˜† ๐—ฏ๐˜† ๐˜๐—ต๐—ฒ ๐—ฐ๐˜‚๐˜€๐˜๐—ผ๐—บ๐—ฒ๐—ฟ.

๐Ÿ“Œ ๐—ข๐—ง๐—œ๐—™%:๐˜๐—ต๐—ถ๐˜€ ๐—บ๐—ฒ๐—ฎ๐˜€๐˜‚๐—ฟ๐—ฒ ๐—ถ๐˜€ ๐—บ๐—ฒ๐—ฎ๐˜€๐˜‚๐—ฟ๐—ฒ๐—ฑ ๐—ฎ๐˜ ๐˜๐—ต๐—ฒ ๐—ผ๐—ฟ๐—ฑ๐—ฒ๐—ฟ ๐—น๐—ฒ๐˜ƒ๐—ฒ๐—น. ๐—œ๐˜ ๐—ฑ๐—ฒ๐˜๐—ฒ๐—ฟ๐—บ๐—ถ๐—ป๐—ฒ๐˜€ ๐—ถ๐—ณ ๐—ฎ๐—ป ๐—ผ๐—ฟ๐—ฑ๐—ฒ๐—ฟ ๐—ถ๐˜€ ๐—ฑ๐—ฒ๐—น๐—ถ๐˜ƒ๐—ฒ๐—ฟ๐—ฒ๐—ฑ ๐—•๐—ข๐—ง๐—› ๐—ถ๐—ป ๐—ณ๐˜‚๐—น๐—น ๐—ฎ๐—ป๐—ฑ ๐—ข๐—ป ๐—ง๐—ถ๐—บ๐—ฒ ๐—ฎ๐˜€ ๐—ฝ๐—ฒ๐—ฟ ๐˜๐—ต๐—ฒ ๐—ฐ๐˜‚๐˜€๐˜๐—ผ๐—บ๐—ฒ๐—ฟ ๐—ผ๐—ฟ๐—ฑ๐—ฒ๐—ฟ ๐—ฟ๐—ฒ๐—พ๐˜‚๐—ฒ๐˜€๐˜.

๐—ง๐—ต๐—ถ๐—ป๐—ด๐˜€ ๐—œ ๐—น๐—ฒ๐—ฎ๐—ฟ๐—ป๐—ฒ๐—ฑ ๐—ณ๐—ฟ๐—ผ๐—บ ๐˜๐—ต๐—ถ๐˜€ ๐—ฝ๐—ฟ๐—ผ๐—ท๐—ฒ๐—ฐ๐˜:-

  1. Did some study on ๐—ธ๐—ฒ๐˜† ๐—ฃ๐—ฒ๐—ฟ๐—ณ๐—ผ๐—ฟ๐—บ๐—ฎ๐—ป๐—ฐ๐—ฒ ๐—œ๐—ป๐—ฑ๐—ถ๐—ฐ๐—ฎ๐˜๐—ผ๐—ฟ๐˜€ ๐—ณ๐—ผ๐—ฟ ๐˜๐—ต๐—ฒ Supply Chain ๐—œ๐—ป๐—ฑ๐˜‚๐˜€๐˜๐—ฟ๐˜† and created ๐——๐—”๐—ซ ๐—บ๐—ฒ๐—ฎ๐˜€๐˜‚๐—ฟ๐—ฒ๐˜€ for the same.
  2. Effective usage of DAX.
  3. Creating calculated columns.
  4. Data Modelling

๐Ÿ“Œ ๐—œ๐—บ๐—ฝ๐—ผ๐—ฟ๐˜๐—ฎ๐—ป๐˜ ๐—ž๐—ฃ๐—œ'๐˜€ ๐—œ๐—ป ๐—›๐—ผ๐˜€๐—ฝ๐—ถ๐˜๐—ฎ๐—น๐—ถ๐˜๐˜† ๐—ฑ๐—ผ๐—บ๐—ฎ๐—ถ๐—ป

๐Ÿ’ก ๐—ฅ๐—ฒ๐˜ƒ๐—ฃ๐—”๐—ฅ (๐—ฅ๐—ฒ๐˜ƒ๐—ฒ๐—ป๐˜‚๐—ฒ ๐—ฃ๐—ฒ๐—ฟ ๐—”๐˜ƒ๐—ฎ๐—ถ๐—น๐—ฎ๐—ฏ๐—น๐—ฒ ๐—ฅ๐—ผ๐—ผ๐—บ): ๐—œ๐˜ ๐—ฐ๐—ฎ๐—น๐—ฐ๐˜‚๐—น๐—ฎ๐˜๐—ฒ๐˜€ ๐˜๐—ต๐—ฒ ๐—ฎ๐˜ƒ๐—ฒ๐—ฟ๐—ฎ๐—ด๐—ฒ ๐—ฟ๐—ฒ๐˜ƒ๐—ฒ๐—ป๐˜‚๐—ฒ ๐—ฒ๐—ฎ๐—ฟ๐—ป๐—ฒ๐—ฑ ๐—ฝ๐—ฒ๐—ฟ ๐—ฟ๐—ผ๐—ผ๐—บ, ๐˜„๐—ต๐—ฒ๐˜๐—ต๐—ฒ๐—ฟ ๐—ถ๐˜'๐˜€ ๐˜€๐—ผ๐—น๐—ฑ ๐—ผ๐—ฟ ๐—ป๐—ผ๐˜, ๐Ÿ“Œ ๐—ฅ๐—ฒ๐˜ƒ๐—ฃ๐—”๐—ฅ: ๐—ง๐—ผ๐˜๐—ฎ๐—น ๐—ฅ๐—ฒ๐˜ƒ๐—ฒ๐—ป๐˜‚๐—ฒ ๐—ฒ๐—ฎ๐—ฟ๐—ป๐—ฒ๐—ฑ ๐—ณ๐—ฟ๐—ผ๐—บ ๐—ฟ๐—ผ๐—ผ๐—บ ๐˜€๐—ฎ๐—น๐—ฒ๐˜€/๐˜๐—ผ๐˜๐—ฎ๐—น ๐—ป๐˜‚๐—บ๐—ฏ๐—ฒ๐—ฟ ๐—ผ๐—ณ ๐—ฎ๐˜ƒ๐—ฎ๐—ถ๐—น๐—ฎ๐—ฏ๐—น๐—ฒ ๐—ฟ๐—ผ๐—ผ๐—บ๐˜€.

๐Ÿ’ก ๐—”๐——๐—ฅ (๐—”๐˜ƒ๐—ฒ๐—ฟ๐—ฎ๐—ด๐—ฒ ๐——๐—ฎ๐—ถ๐—น๐˜† ๐—ฅ๐—ฎ๐˜๐—ฒ): ๐—”๐——๐—ฅ ๐—บ๐—ฒ๐—ฎ๐˜€๐˜‚๐—ฟ๐—ฒ๐˜€ ๐˜๐—ต๐—ฒ ๐—ฎ๐˜ƒ๐—ฒ๐—ฟ๐—ฎ๐—ด๐—ฒ ๐—ฝ๐—ฟ๐—ถ๐—ฐ๐—ฒ ๐—ผ๐—ฟ ๐—ฟ๐—ฎ๐˜๐—ฒ ๐˜๐—ต๐—ฎ๐˜ ๐—ฎ ๐—ต๐—ผ๐˜๐—ฒ๐—น ๐—ฐ๐—ต๐—ฎ๐—ฟ๐—ด๐—ฒ๐˜€ ๐—ณ๐—ผ๐—ฟ ๐—ถ๐˜๐˜€ ๐—ฟ๐—ผ๐—ผ๐—บ๐˜€ ๐—ฝ๐—ฒ๐—ฟ ๐—ฑ๐—ฎ๐˜†. ๐—œ๐˜'๐˜€ ๐—ฐ๐—ฎ๐—น๐—ฐ๐˜‚๐—น๐—ฎ๐˜๐—ฒ๐—ฑ ๐—ฏ๐˜† ๐—ฑ๐—ถ๐˜ƒ๐—ถ๐—ฑ๐—ถ๐—ป๐—ด ๐˜๐—ต๐—ฒ ๐˜๐—ผ๐˜๐—ฎ๐—น ๐—ฟ๐—ฒ๐˜ƒ๐—ฒ๐—ป๐˜‚๐—ฒ ๐—ฒ๐—ฎ๐—ฟ๐—ป๐—ฒ๐—ฑ ๐—ณ๐—ฟ๐—ผ๐—บ ๐—ฟ๐—ผ๐—ผ๐—บ ๐˜€๐—ฎ๐—น๐—ฒ๐˜€ ๐—ฏ๐˜† ๐˜๐—ต๐—ฒ ๐˜๐—ผ๐˜๐—ฎ๐—น ๐—ป๐˜‚๐—บ๐—ฏ๐—ฒ๐—ฟ ๐—ผ๐—ณ ๐—ฟ๐—ผ๐—ผ๐—บ๐˜€ ๐˜€๐—ผ๐—น๐—ฑ. ๐Ÿ“Œ ๐—”๐——๐—ฅ = ๐—ง๐—ผ๐˜๐—ฎ๐—น ๐—ฅ๐—ฒ๐˜ƒ๐—ฒ๐—ป๐˜‚๐—ฒ / ๐—ก๐˜‚๐—บ๐—ฏ๐—ฒ๐—ฟ ๐—ผ๐—ณ ๐—ฅ๐—ผ๐—ผ๐—บ๐˜€ ๐—ฆ๐—ผ๐—น๐—ฑ

๐Ÿ’ก ๐—ฅ๐—ฒ๐˜ƒ๐—ฒ๐—ป๐˜‚๐—ฒ ๐—ฅ๐—ฒ๐—ฎ๐—น๐—ถ๐˜‡๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—ฃ๐—ฒ๐—ฟ๐—ฐ๐—ฒ๐—ป๐˜๐—ฎ๐—ด๐—ฒ = (๐—”๐—ฐ๐˜๐˜‚๐—ฎ๐—น ๐—ฅ๐—ฒ๐˜ƒ๐—ฒ๐—ป๐˜‚๐—ฒ / ๐—ฃ๐—ผ๐˜๐—ฒ๐—ป๐˜๐—ถ๐—ฎ๐—น ๐—ฅ๐—ฒ๐˜ƒ๐—ฒ๐—ป๐˜‚๐—ฒ) * ๐Ÿญ๐Ÿฌ๐Ÿฌ

๐Ÿ’ก ๐—ก๐—ผ-๐—ฆ๐—ต๐—ผ๐˜„ ๐—ฅ๐—ฎ๐˜๐—ฒ: ๐—ง๐—ต๐—ฒ ๐—ป๐—ผ-๐˜€๐—ต๐—ผ๐˜„ ๐—ฟ๐—ฎ๐˜๐—ฒ ๐—ถ๐˜€ ๐˜๐—ต๐—ฒ ๐—ฝ๐—ฒ๐—ฟ๐—ฐ๐—ฒ๐—ป๐˜๐—ฎ๐—ด๐—ฒ ๐—ผ๐—ณ ๐—ฟ๐—ฒ๐˜€๐—ฒ๐—ฟ๐˜ƒ๐—ฎ๐˜๐—ถ๐—ผ๐—ป๐˜€ ๐˜๐—ต๐—ฎ๐˜ ๐—ฟ๐—ฒ๐˜€๐˜‚๐—น๐˜ ๐—ถ๐—ป ๐—ด๐˜‚๐—ฒ๐˜€๐˜๐˜€ ๐—ป๐—ผ๐˜ ๐˜€๐—ต๐—ผ๐˜„๐—ถ๐—ป๐—ด ๐˜‚๐—ฝ. ๐Ÿ“Œ ๐—ก๐—ผ-๐—ฆ๐—ต๐—ผ๐˜„ ๐—ฅ๐—ฎ๐˜๐—ฒ = (๐—ก๐˜‚๐—บ๐—ฏ๐—ฒ๐—ฟ ๐—ผ๐—ณ ๐—ก๐—ผ-๐—ฆ๐—ต๐—ผ๐˜„๐˜€ / ๐—ง๐—ผ๐˜๐—ฎ๐—น ๐—•๐—ผ๐—ผ๐—ธ๐—ถ๐—ป๐—ด๐˜€) * ๐Ÿญ๐Ÿฌ๐Ÿฌ

๐Ÿ’ก ๐——๐—ฆ๐—ฅ๐—ก :๐—ง๐—ต๐—ถ๐˜€ ๐—บ๐—ฒ๐˜๐—ฟ๐—ถ๐—ฐ๐˜€ ๐˜๐—ฒ๐—น๐—น๐˜€ ๐—ผ๐—ป ๐—ฎ๐˜ƒ๐—ฒ๐—ฟ๐—ฎ๐—ด๐—ฒ ๐—ต๐—ผ๐˜„ ๐—บ๐—ฎ๐—ป๐˜† ๐—ฟ๐—ผ๐—ผ๐—บ๐˜€ ๐—ฎ๐—ฟ๐—ฒ ๐—ฟ๐—ฒ๐—ฎ๐—ฑ๐˜† ๐˜๐—ผ ๐˜€๐—ฒ๐—น๐—น ๐—ณ๐—ผ๐—ฟ ๐—ฎ ๐—ฑ๐—ฎ๐˜† ๐—ฐ๐—ผ๐—ป๐˜€๐—ถ๐—ฑ๐—ฒ๐—ฟ๐—ถ๐—ป๐—ด ๐—ฎ ๐˜๐—ถ๐—บ๐—ฒ ๐—ฝ๐—ฒ๐—ฟ๐—ถ๐—ผ๐—ฑ. ๐Ÿ“Œ ๐——๐—ฆ๐—ฅ๐—ก=๐—ง๐—ผ๐˜๐—ฎ๐—น ๐—–๐—ฎ๐—ฝ๐—ฎ๐—ฐ๐—ถ๐˜๐˜†/๐—ก๐—ผ ๐—ผ๐—ณ ๐—ฑ๐—ฎ๐˜†๐˜€.

๐—ง๐—ต๐—ถ๐—ป๐—ด๐˜€ ๐—œ ๐—น๐—ฒ๐—ฎ๐—ฟ๐—ป๐—ฒ๐—ฑ ๐—ณ๐—ฟ๐—ผ๐—บ ๐˜๐—ต๐—ถ๐˜€ ๐—ฝ๐—ฟ๐—ผ๐—ท๐—ฒ๐—ฐ๐˜:-

  1. Did some study on ๐—ธ๐—ฒ๐˜† ๐—ฃ๐—ฒ๐—ฟ๐—ณ๐—ผ๐—ฟ๐—บ๐—ฎ๐—ป๐—ฐ๐—ฒ ๐—œ๐—ป๐—ฑ๐—ถ๐—ฐ๐—ฎ๐˜๐—ผ๐—ฟ๐˜€ ๐—ณ๐—ผ๐—ฟ ๐˜๐—ต๐—ฒ ๐—›๐—ผ๐˜€๐—ฝ๐—ถ๐˜๐—ฎ๐—น๐—ถ๐˜๐˜† ๐—œ๐—ป๐—ฑ๐˜‚๐˜€๐˜๐—ฟ๐˜† and created๐——๐—”๐—ซ ๐—บ๐—ฒ๐—ฎ๐˜€๐˜‚๐—ฟ๐—ฒ๐˜€ for the same.
  2. Effective usage of DAX.
  3. Creating calculated columns.
  4. Data Modelling.
  • Technologies used: Power BI,Excel,Dax,Data Modelling

๐—–๐—ผ๐—ป๐—ฐ๐—น๐˜‚๐˜€๐—ถ๐—ผ๐—ป:

  1. Total Revenue is overall $๐Ÿญ.๐Ÿฒ๐Ÿต๐—•
  2. ADR is ๐—ฅ๐˜€ ๐Ÿญ๐Ÿฎ,๐Ÿฒ๐Ÿต๐Ÿฒ 3.RevPAR is ๐—ฅ๐˜€ ๐Ÿณ,๐Ÿฏ๐Ÿฏ๐Ÿณ
  3. The occupancy rate is ๐Ÿฑ๐Ÿณ.๐Ÿณ๐Ÿต%
  4. Realization rate is ๐Ÿด๐Ÿฌ.๐Ÿญ๐Ÿด%
  5. Cancellation rate is ๐Ÿฎ๐Ÿฐ.๐Ÿด๐Ÿฐ%
  6. Mumbai has the highest RevPAR Booking ๐Ÿญ๐Ÿฑ.๐Ÿฏ๐Ÿต๐—ž
  7. Hyderabad has the lowest RevPAR ๐Ÿต.๐Ÿฏ๐Ÿฎ๐—ธ Booking
  8. Elite has the highest Revenue contribution per Room Class ๐Ÿฏ๐Ÿฎ.๐Ÿณ๐Ÿต%.
  9. Standard has the lowest Revenue contribution per Room Class ๐Ÿญ๐Ÿด.๐Ÿญ๐Ÿฎ%

Linkedin Engagement

Project Link:- Marketing Insights

About Challenge: Domain: F & B Function: Marketing
CodeX is a German beverage company aiming to make its mark in the Indian market. A few months ago, they launched their energy drink in 10 cities in India. Their Marketing team is responsible for increasing brand awareness, market share, and product development. They conducted a survey in those 10 cities and received results from 10k respondents.

Task Completed

  1. Demographic Insights Key Insights: 1.1 Among 10 thousand respondents, 6038 are male, indicating a 60% preference for energy drinks. 1.2 Survey results reveal energy drinks' popularity among youngsters, with over 50% aged 19-30; considering ages 15-30 raises the percentage to 70%

  2. Consumer Preferences: Key Insights: 2.1 Caffeine, known for enhancing attention and alertness, is the primary anticipated ingredient in energy drinks, closely followed by vitamins 2.2 Compact & Portable Cans are in high demand, trailed by Innovative Bottle Designs.

  3. Competition Analysis: Key Insights: 3.1 The top reason for choosing the brands by consumers is brand reputation. 3.2 "Sky9" is notably effective, "Gangster" is remarkably healthy, while "Bepsi" raises concerns for being more dangerous.

  4. Marketing Channels and Brand Awareness: Key Insights: 4.1 Online ads prove highly effective for reaching a wide audience swiftly and economically, as observed earlier

  5. Brand Penetration: Key Insights 5.1 Among 980 individuals, 455 are familiar with our brand, aligning their average taste rating of 3.3 with the industry average

  6. Purchase Behavior: Key Insights 6.1 Supermarkets are the predominant choice for consumers purchasing energy drinks. 6.2 Sports, exercise, and studying/working late; this data underscores greater youth consumption. 6.3 40% of consumers anticipate no packaging change, while 39% are receptive to experimenting with Limited Edition Packaging.

  7. Product Development Key Insights 7.1 We should increase Effectiveness 7.2 We should improve and Reduce Sugar Conten

Let's Connect! ๐ŸŒ

  • LinkedIn: Suraj Gusain

  • Medium:Suraj Gusain

  • My Portfolio

  • My Power BI Projects

  • MY Leetcode Profile

  • ๐Ÿ“ซ How to reach me: ...surajgusain002@gmail.com

  • ๐Ÿ‘ฏ Iโ€™m looking to job in Data Analyst

    • โšก Fun fact: Did you know that I've not only aced the challenges of B.Tech studies but also delved into the world of data analysis, attempting the GATE exam with determination? With a passion for continuous learning and an enthusiasm for exploring the data-driven universe, every project and certification I complete is a step closer to mastering the art of data analytics! ๐Ÿš€๐Ÿ“Š

Pinned Loading

  1. FAASO_SQL_ANALYSIS_PROJECT FAASO_SQL_ANALYSIS_PROJECT Public

    Rebel Foods, formerly known as Faasos, is a renowned food delivery company in India. It originated as a restaurant chain but transitioned into an online platform. Rebel Foods is known for providingโ€ฆ

    2

  2. ZOMATO_EDA_WITH_PYTHON_AND_SQL ZOMATO_EDA_WITH_PYTHON_AND_SQL Public

    Explore restaurant scene in 3 Indian metros (174 restaurants). Valuable resource for researchers, analysts & food enthusiasts to study dining & delivery ratings, preferences, cuisines, pricing, treโ€ฆ

    Jupyter Notebook 1

  3. PowerBi-Project-Marketing-Insights PowerBi-Project-Marketing-Insights Public

    About Challenge: Domain: F & B Function: Marketing CodeX is a German beverage company aimig to make its mark in the Indian market. A few months ago, they launched their energy drink in 10 cities inโ€ฆ

    1

  4. IPL-PROJECT-WEBSITE IPL-PROJECT-WEBSITE Public

    IPL EDA (Exploratory Data Analysis) was conducted, revealing valuable insights. The analysis focused on various aspects such as player performance, team statistics, and match outcomes. Key findingsโ€ฆ

    Python 1

  5. NETFLIX-EDA-PROJECT NETFLIX-EDA-PROJECT Public

    The Netflix EDA Project uncovers insights from streaming data to enhance content strategy. Analyzing genres, user behavior, and regional variations, it informs decision-making, improves user experiโ€ฆ

    Jupyter Notebook 1

  6. Asia-Cup-SQL-Data-Analysis Asia-Cup-SQL-Data-Analysis Public

    "Unveiling the Secrets of Asia Cup: A Journey Through Data Analysis! ๐Ÿ๐Ÿ“Š Dive deep into the heart of the ๐—”๐˜€๐—ถ๐—ฎ ๐—–๐˜‚๐—ฝ ๐˜„๐—ถ๐˜๐—ต ๐—ผ๐˜‚๐—ฟ ๐—น๐—ฎ๐˜๐—ฒ๐˜€๐˜ ๐—ฆ๐—ค๐—Ÿ ๐—ฑ๐—ฎ๐˜๐—ฎ ๐—ฎ๐—ป๐—ฎ๐—น๐˜†๐˜€๐—ถ๐˜€ ๐—ฝ๐—ฟ๐—ผ๐—ท๐—ฒ๐—ฐ๐˜โ— ๐ŸŒ๐Ÿ” From thrilling matches to strategic plโ€ฆ