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Data Analyst with less than a year in data cleaning, EDA & dashboard development
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Results-driven Data Analyst and 2026 B.E. Computer Science graduate with hands-on experience in data cleaning, exploratory data analysis (EDA), MIS reporting, and dashboard development. Proficient in Excel (Pivot Tables, VLOOKUP, Slicers), Power BI (DAX, Power Query, data modeling), SQL (MySQL), and Python. Built 2 end-to-end analytics projects delivering actionable business insights from 1,000+ records. Adept at transforming raw data into interactive dashboards, KPI reports, and data-driven recommendations that support cross-functional decision-making.
Vivekanandha College of Technology for Women, Tiruchengode (Anna University)
B.E. Computer Science & Engineering · Computer Science & Engineering
January 1, 2022 – January 1, 2026
Government Higher Secondary School, Keeripatty, Salem
HSC (Class XII)
January 1, 2022 – January 1, 2022
Government Higher Secondary School, Keeripatty, Salem
SSLC (Class X)
January 1, 2020 – January 1, 2020
Cybernaut Edtech
Data Analyst Intern
February 1, 2026 – April 1, 2026
India
Superstore Sales Analytics Dashboard
January 1, 2026 – January 1, 2026
Designed an end-to-end Power BI dashboard tracking KPIs – sales, profit, and order volumes – across 3 regions and multiple product categories, replacing manual Excel-based reporting for monthly business reviews. Applied DAX formulas, Power Query transformations, and data modeling to analyse performance across geographies and product lines; identified loss-making segments and underperforming regions. Delivered actionable recommendations on margin improvement strategies by highlighting underperforming categories with visual drill-throughs and comparative KPI cards. Dashboard adopted by stakeholders for monthly business reviews, fully replacing manual Excel-based reporting and saving hours of manual effort each cycle.
Bike Buyers Analytics Dashboard
January 1, 2026 – January 1, 2026
Analysed 1,000+ customer records to uncover bike purchasing patterns; identified mid-age buyers (39-59 yrs) as the highest-value segment, accounting for 54% of all purchases. Performed data cleaning, age-group segmentation (Adult / Mid-Age / Old), and Pivot Table modeling; found buyers earn an average of $57,963 vs $54,875 for non-buyers – a $3,000+ income gap driving purchasing propensity. Built an interactive Excel dashboard with slicers for region, occupation, and marital status, enabling self-serve market segmentation analysis by marketing teams. Insights used to define targeting strategy: North America (51% of dataset), Professionals, and homeowners identified as primary buyer segments - directly informing campaign prioritisation.
GenAI Powered Data Analytics Job Simulation
TATA / Forage
June 1, 2026 – Present
HTML and Java Training
IIT Bombay (E-learning)
June 1, 2026 – Present
Artificial Intelligence Fundamentals
IBM SkillsBuild
June 1, 2026 – Present
Basics of Python
Infosys Springboard
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, including sales analytics and customer behavior analysis, shows a broad interest in applying data analysis across different business domains. Their internship experience and personal projects align well with the target role of Data Analyst, indicating a proactive and self-driven approach to skill development. The certifications in AI and Python also suggest a willingness to learn and adapt to new technologies, contributing positively to cultural fit.
Soft Skills & Operational Fit
The candidate demonstrates strong soft skills such as analytical thinking, problem-solving, attention to detail, communication, and teamwork, which are essential for a data analyst role. Their experience in stakeholder management and delivering actionable recommendations indicates a good operational fit for roles requiring interaction with business teams.