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Entry-level Power BI Developer with strong data analysis skills.
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Assessing your cultural and operational fit
Aspiring Data Analyst with a solid command of the modern data stack — Python (Pandas, NumPy), SQL, Power BI, and Excel. Capable of end-to-end data workflows: from data extraction and transformation to visualization and reporting. Passionate about uncovering patterns in data and translating them into clear, business-ready insights. Ready to contribute to data-driven teams as a dedicated entry-level analyst.
T.B.M.L. Arts and Science College
Bachelor of Computer Applications (BCA) · Computer Applications
August 1, 2022 – June 30, 2025
Super Store Sales & Profit Dashboard
June 1, 2026 – Present
Built a 2-page interactive Power BI dashboard on 5,000+ retail orders spanning 2023–2026, analyzing $2.33M in sales, $292.3K profit, and 39K units across 3 categories, 4 regions, and 50 US states. Designed 8 DAX measures including RANKX for Top-10 state rankings, SAMEPERIODLASTYEAR for YoY growth, CALCULATE for segment-level filtering, and DIVIDE for profit margin (12.56%) and return rate calculations. Built a Star Schema data model in Power Query — cleaned nulls, cast data types, created a Date dimension table, and established 1:Many relationships between Orders, Returns, and Date tables for optimized DAX performance. Designed Page 1 with Sales Overview visuals: KPI cards, treemap (3 categories × sub-categories), segment donut, region bar chart, ship-mode distribution, and monthly sales line chart — with 3 interactive slicers (Category, Region, Returned). Built Page 2 as a Regional & Customer Drill-through: geographic map (US states), Top-10 states by Sales and Profit, monthly profit bar chart, and a granular order-level detail table with Order ID, Customer, Product, State, and Returned flag. Uncovered that Technology category contributes 43% of total revenue, the West region leads all 4 regions, California tops both sales (~$0.50M) and profit (~$50K), and 60.04% of orders ship via Standard Class.
AI Job Market Analysis Dashboard
June 1, 2026 – Present
Built an AI Job Market Analysis Dashboard in Power BI analyzing 2,000 AI job records across 8 job roles, 2,000+ companies, and global locations to identify hiring trends and salary benchmarks. Preprocessed raw data using Python (Pandas & NumPy) — handled missing values, standardized categorical fields (experience_level encoding), performed feature engineering (salary bands, remote ratio flags), and exported clean CSV for Power BI ingestion. Developed DAX measures including RANKX for role ranking, CALCULATE for experience-level segmentation, and DIVIDE for percentage distributions; modeled data using a Star Schema for optimized query performance. Designed interactive visuals: KPI cards, horizontal bar charts, donut charts, geographic map, and column charts — with 4 slicers (Job Title, Location, Company, Experience Level) enabling multi-dimensional filtering. Uncovered that Data Analyst is the #1 demanded AI role (271 openings), 35.1% of jobs target Entry Level candidates, and the market average salary is $171K — enabling job seekers to prioritize high-opportunity roles.
View ProjectSwift Route Logistics Analysis Dashboard
June 1, 2026 – Present
Built a 4-page interactive Power BI dashboard for a logistics company tracking end-to-end delivery operations. Visualized key KPIs — Total Orders (27,979), On-Time Delivery Rate, CSAT %, and Average Delivery Time with Month-over-Month comparison. Designed Drivers Overview page analyzing delayed delivery rates across 55 drivers and experience vs. performance ratings. Created Hubs Overview with hub capacity vs. orders processed and a heat map showing processing hours across 6 hubs (Mon–Sun). Built Vehicles Overview tracking 45 vehicles — active vs. maintenance status, breakdown by vehicle model, and orders by vehicle type. Implemented dynamic filters (Year & Month slicers) and page navigation buttons for seamless user experience.
Self-learning in Data Analyst, Excel, and Visualization
Unknown
June 1, 2026 – Present
Internship Certificate
A1Technoskill
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's portfolio demonstrates a strong initiative for self-learning and practical application through personal projects. The diversity of projects (logistics, retail sales, AI job market) indicates adaptability and a broad interest in applying data analysis across different domains. This proactive approach and project-driven learning suggest a good fit for a dynamic, results-oriented team. The focus on Power BI and related data skills directly aligns with the target role.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to translate raw data into business insights, suggesting analytical thinking and problem-solving skills. The structured approach to dashboard development and data modeling implies attention to detail and organizational skills. However, without direct interview data, assessment of collaboration, communication, and stress handling is limited.