Data Analyst with 1+ years in Power BI, SQL & Python
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Data Analyst with hands-on experience building end-to-end dashboards and analytical solutions using SQL, Power BI, Excel, and Python. Developed business intelligence projects analyzing ₹2.94M+ sales data, departmental budgets, and 479K+ global job market records. Skilled in data cleaning, KPI reporting, DAX, data modeling, and translating complex datasets into actionable business insights.
Sethu Institute of Technology
B.E. · Computer Science and Engineering
August 1, 2021 – June 30, 2025
Innovel Training | Placement Institute
Data Analytics Trainee
August 1, 2025 – March 31, 2026
Madurai, Tamil Nadu, India
Genz Educate Wing
Business Development Trainee
January 1, 2025 – February 28, 2025
Bengaluru, Karnataka, India
Tarcin Robotic LLP
Full Stack Development Intern
June 1, 2023 – June 15, 2023
Madurai, Tamil Nadu, India
Regional Sales Performance Dashboard
June 21, 2026 – Present
• Developed a 4-page Power BI dashboard to track sales performance, target achievement, manager effectiveness, and operational risk across regions and categories. • Built KPI dashboards monitoring ₹2.94M Sales, ₹372.8K Profit, 4,596 Orders, and 38K Units Sold. • Created DAX measures for Sales YoY (54.98%), Profit YoY (52.88%), Target Achievement (101.7%), and operational risk analysis. • Designed manager scorecards, heatmaps, gauges, and drill-down reports to evaluate category performance and target attainment. • Generated insights identifying the Central region as the top revenue contributor and Technology as the best-performing category (119.6% achievement). • Built a star-schema data model integrating Orders, Returns, Calendar, and People datasets to enable accurate cross functional sales analysis. • Implemented interactive slicers, drill-through navigation, and dynamic KPI tracking, allowing users to analyze performance by region, manager, category, and time period.
Department Budget & Financial Analysis Dashboard
June 21, 2026 – Present
• Identified the core business problem – departments managing budgets across scattered datasets with no centralized visibility – and Built an end-to-end BI solution to solve it. • Developed SQL data pipelines using CTEs and multi-table joins to consolidate multiple department datasets into a single unified data model, reducing manual data preparation time by 30%. • Built a star schema data model in Power BI to ensure clean, scalable relationships between fact and dimension tables across all 5 departments. • Developed custom DAX measures and calculated columns to track real-time KPIs – Budget Utilization (39.6%), Total Expense (₹1.37M), and Remaining Capital (₹2.08M). • Designed a Project Overview dashboard displaying department-wise project cost, salary cost, capital distribution, and project status breakdowns using interactive donut and bar visuals. • Built a Financial Risk & Performance dashboard with budget vs. expense comparisons, salary vs. project cost analysis, and a gauge-style risk indicator showing Low Risk status. • Automated a Risk Status alert system using DAX logic to flag any department exceeding its monthly spend threshold – all 5 departments maintained Safe status throughout the period. • Generated business insights: Engineering holds the highest budget allocation (12L), Sales has the highest utilization rate, and overall organization-wide budget health remains at Low Risk with ₹2.08M in remaining capital.
Global Data Job Market Analysis Dashboard
June 21, 2026 – Present
• Sourced and processed a 479K-record global job listings dataset in Excel, performing thorough data cleaning, deduplication, and transformation before loading into Power BI. • Built an interactive main dashboard displaying total job count (479K), median yearly salary ($113K), median hourly rate ($48), and average job rating — all with dynamic filtering by job title. • Designed a Job Over Time line chart tracking monthly job posting trends across Jan-Nov 2024, revealing fluctuations and demand peaks across the data job market. • Created a Job Count bar chart ranking 10 data roles by demand – Data Engineer (129K), Data Analyst (113K), and Data Scientist (98K) emerging as the top three. • Built an Hourly vs. Median Salary scatter chart to visually correlate yearly salary with hourly rate across all roles, identifying Machine Learning Engineer and Senior Data Engineer as the highest total compensation roles. • Implemented a drill-through Job Title page enabling role-specific deep dives – revealing work-from-home %, no-degree-mention %, health insurance %, preferred job platforms, and schedule type (89% full-time for Data Engineers). • Surfaced a key strategic insight: Senior-level roles command 30-70% salary premiums over junior counterparts – Senior Data Scientist ($156K) vs. Data Scientist ($125K), and Senior Data Analyst ($107K) vs. Data Analyst ($90K). • Identified that 85% of data roles globally are on-site with only 15% remote, and LinkedIn dominates as the primary hiring platform – providing actionable intelligence for candidates planning their job search strategy.
Data Analytics Simulation
Deloitte
April 1, 2026 – Present
Introduction to MS Excel
Microsoft
April 1, 2026 – Present
Power BI Certification
Innovel
January 1, 2026 – Present
MySQL Certification
Innovel
December 1, 2025 – Present
Python Certification
Innovel
August 1, 2025 – Present
Azure Fundamentals (AZ-900)
Microsoft
July 1, 2023 – Present
Cultural Fit Analysis
The candidate's projects demonstrate a strong alignment with the Data Analyst role, covering sales, financial, and market analysis. The diversity of projects (sales, budget, job market) indicates adaptability and a broad interest in applying data analytics across different domains. The certifications in MySQL, Python, Power BI, and Azure Fundamentals show a proactive approach to skill development, which aligns with a growth-oriented culture. However, the experience is primarily from trainee roles and recent certifications, suggesting a need for more hands-on, sustained professional experience.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to identify business problems and develop solutions, suggesting problem-solving skills. The detailed project descriptions also show a structured approach to data analysis and reporting. While direct evidence of teamwork or stress handling is limited, the professional experience as a 'Data Analytics Trainee' implies exposure to a professional work environment.