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Data Analyst with less than a year in Python, SQL, and Excel for data analysis projects.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
BCA graduate (82%) with hands-on experience in Python, SQL, and Excel. Built end-to-end data analysis projects on retail and streaming datasets covering data cleaning, normalization, SQL querying, and visualization. Eager to grow in statistical modelling and applied data science.
University Maharani College, Jaipur
Bachelor of Computer Applications (BCA) · Computer Applications
August 1, 2022 – June 30, 2025
HVN Public School, RBSE
Higher Secondary (12th) · Science
June 1, 2021 – May 31, 2022
Vridha Store Sales Dashboard
July 1, 2024 – September 30, 2024
Cleaned and structured 10,000+ rows of raw retail data handled duplicates, blanks, and inconsistent formatting to ensure data accuracy before analysis. Built an interactive dashboard using Pivot Tables, slicers, and charts to track KPIs across product categories, customer segments, and sales channels. Identified top-performing categories and highlighted a 92% order delivery success rate; surfaced revenue trends to support business decision-making.
Walmart Sales Analysis
April 1, 2024 – June 30, 2024
Queried a large retail sales dataset using JOINS, GROUP BY, CTEs, and window functions to rank products and extract store-level revenue trends. Ranked products by revenue using window functions and identified top-performing store segments and product categories. Used CTEs to structure complex queries into modular, readable blocks - improving maintainability and query performance.
Netflix Data Analysis
January 1, 2024 – March 31, 2024
Built an end-to-end pipeline: loaded raw Excel data into SQL Server via SQLAlchemy, cleaned encoding issues and inconsistent duration formats using Pandas, and normalized multi-valued columns (cast, genres) into relational tables. Wrote advanced SQL queries using CTEs and window functions to deduplicate records, rank top content-producing countries, and aggregate genre and format trends. Produced visualizations (Matplotlib) showing content growth post-2015 and movie vs. TV show distribution across the catalog.
Cultural Fit Analysis
The candidate's academic projects demonstrate a strong interest in data analysis across different domains (retail, streaming). The breadth of tools used (Excel, SQL Server, Python libraries) indicates adaptability. However, without information on extracurricular activities, volunteer work, or team-based academic projects, a comprehensive assessment of cultural fit is limited. The candidate is an aspiring data scientist, which aligns with a growth mindset.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on structured tasks, follow data analysis methodologies, and present findings. The focus on academic projects suggests a learning-oriented individual. However, without professional experience or psychometric test results, it's difficult to assess operational fit, teamwork, or stress handling capabilities.