Data Analyst with less than a year in Data Analytics & Visualization
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Assessing your cultural and operational fit
Motivated and detail-oriented Data Analyst fresher with strong knowledge of data cleaning, data visualization, and statistical analysis. Proficient in SQL, Python, Excel, and Power BI. Passionate about transforming raw data into meaningful insights to support business decision-making.
IFTM University
Bachelor Of Computer Applications (BCA) · Computer Applications
August 1, 2023 – June 1, 2026
Customer Churn Analysis
January 1, 2026 – January 1, 2026
Used SQL queries to extract and analyze customer data. Applied data visualization techniques to identify churn patterns. Provided actionable insights that reduced churn by 10%.
Exploratory Data Analysis using Python
August 1, 2025 – August 1, 2025
Cleaned and preprocessed datasets using Pandas and NumPy. Performed exploratory data analysis to identify trends, patterns, and anomalies. Created visualizations using Matplotlib and Seaborn. Summarized insights in a structured analytical report.
Sales Data Analysis Project
December 1, 2024 – December 1, 2024
Cleaned and analyzed 50,000+ rows of sales data using Python and Pandas. Created interactive dashboard in Power BI. Improved revenue insights leading to 15% increase in sales performance.
Microsoft Power BI Certification
Microsoft
June 1, 2026 – Present
SQL for Data Analysis
Unknown
June 1, 2026 – Present
Google Data Analytics Certification
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a clear focus on data analysis, aligning well with the target role. The diversity of projects (sales, general EDA, customer churn) shows a breadth of application for data analysis skills. The candidate is a fresher, which implies a potential for growth and adaptability within a team, but also a need for mentorship and structured guidance.
Soft Skills & Operational Fit
The candidate's project descriptions highlight an ability to translate data into actionable insights, suggesting a results-oriented approach. The academic nature of projects and lack of professional experience mean operational fit in a corporate environment is yet to be proven. The summary indicates a 'motivated and detail-oriented' individual, which aligns with data analysis roles.