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Data Science with less than a year in Power BI, Python, and SQL.
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Assessing your cultural and operational fit
Aspiring Data Analyst with foundational knowledge in data analysis, visualization, and database management. Currently pursuing a B.Tech in Computer Science (Data Science), I have hands-on experience in Python, Power BI, and MySQL. My projects demonstrate proficiency in EDA, data cleaning, interactive dashboard creation, and web scraping for data collection. Eager to contribute to data-driven decision-making.
G.H.Raisoni College Of Engineering And Business Management
B.Tech in Computer Science · Data Science
August 1, 2022 – June 30, 2026
Weather Data Analysis Dashboard (Power BI)
January 1, 2022 – June 1, 2026
Visualized past weather patterns using Power BI. Performed EDA to identify seasonal patterns and anomalies. Analyzed multi-year weather data including rainfall, temperature, humidity, and wind speed. Created Power BI visualizations and dashboards for metric-wise comparison. Identified seasonal and monthly weather patterns across districts using interactive visuals. Analyzed rainfall and temperature trends to highlight climate variations.
View ProjectLibrary Management Analysis (MySQL)
January 1, 2022 – June 1, 2026
Analyzed and managed library operations using MySQL, focusing on book inventory, member records, book issuance, returns, and overdue tracking to improve data accuracy and operational efficiency. Designed and worked with relational database tables for books, book copies, members, authors, publishers, and branch, book loans. Performed analysis on: Book availability and issued books, Member borrowing patterns, Frequently issued books and categories, Overdue and return status. Optimized queries to improve performance and readability. Ensured data integrity using primary keys and foreign keys. Identified most borrowed books and popular categories. Analyzed member activity trends and borrowing frequency.
View ProjectRoad Accident Dashboard (MS Excel)
January 1, 2022 – June 1, 2026
Analyzed road accident data and identified casualty trends, severity levels, vehicle involvement, road conditions, and environmental factors using an interactive Excel dashboard to support data-driven decision making. Cleaned and prepared raw accident data using Excel data preprocessing techniques. Used Pivot Table and Pivot Charts to summarize accident and casualty metrics. Created interactive KPI cards to display: Total casualties, Fatal, serious, and slight casualties. Built dynamic visualizations to analyze: Casualties by vehicle type, Casualties by road type and road surface, Casualties by light condition and location (urban vs rural), Current year vs previous year monthly trends. Implemented Slicers and Timelines for interactive filtering by: Date, Area type (Urban / Rural). Identified that cars account for the highest number of road accident casualties. Found that slight casualties form the majority of total casualties.
View ProjectTravel & Tourism Data Analysis – Web Scraping & Python EDA
January 1, 2022 – June 1, 2026
Collected and analyzed travel and tourism package data through web scraping and Python-based exploratory data analysis (EDA) to identify pricing trends, popular destinations, and package characteristics. Scraped travel package data from TravelTriangle using Python web scraping tools. Extracted structured information such as package name, duration, price, discounts, destinations, hotel ratings, and activities. Cleaned and preprocessed raw data by handling missing values, duplicates, and inconsistent formats. Performed EDA using Pandas and NumPy to uncover patterns and trends. Created visualizations using Matplotlib and Seaborn to analyze pricing, duration, and destination popularity. Identified popular travel destinations and frequently offered packages. Analyzed price variations based on package duration and destination.
View ProjectPower BI
Unknown
June 1, 2026 – Present
MySQL for Data Analytics – Certified
Unknown
June 1, 2026 – Present
Exploratory Data Analysis (EDA) with Python – Certified
Unknown
June 1, 2026 – Present
Python for Data Analysis – Certified
Unknown
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a breadth of interest in various data analysis applications, from library management to travel and tourism, and road accidents. This diversity suggests adaptability and a willingness to explore different problem domains. The alignment with a 'Data Science' target role is clear through the chosen projects and certifications. However, without information on extracurricular activities or team-based project contributions, a deeper assessment of cultural fit is limited.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work through structured analytical tasks, suggesting a methodical approach. The focus on academic projects implies a learning-oriented mindset. However, without direct work experience or psychometric test results, it is difficult to assess stress handling, team collaboration, or broader operational fit.