Data Analyst with less than a year in SQL, Python, and Power BI
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Assessing your cultural and operational fit
Data/Business Analyst fresher with hands-on project experience in SQL, Power BI (DAX, Power Query), Python (Pandas, NumPy, Seaborn), and Advanced Excel (VLOOKUP, Pivot Tables, VBA). Experienced in ETL pipelines, data validation, EDA, KPI development, and MIS reporting on 100K+ records. Skilled at translating business requirements into actionable insights and presenting findings to stakeholders for data-driven decision making.
S.R.T.M. University
Bachelor of Computer Application (B.C.A) · Computer Application
N/A – June 30, 2026
Video Streaming Quality & Buffering KPI Dashboard
January 1, 2026 – Present
Validated 2,000+ streaming session records using SQL (IS NULL checks, row reconciliation) — cross-referencing logs, buffering events, and customer feedback to ensure 99%+ data accuracy. Transformed raw data using Power Query (unpivoting columns, date formatting, data model relationships); created 6 DAX measures Playback Success Rate, Avg Buffer Duration, CSAT by Region. Built an interactive Power BI dashboard with slicers, drill-through pages, and conditional KPI cards enabling stakeholders to identify service quality issues 40% faster than the prior Excel report.
View ProjectCustomer Churn Analysis E-Commerce Platform (Olist)
January 1, 2026 – Present
Merged 6 CSV tables (orders, customers, reviews, payments) using Pandas and SQL joins to build a unified 100K+ record dataset for churn analysis. Used SQL to group orders by delivery delay buckets (0-2 days, 3–5 days, >5 days) and discovered customers with delays >5 days churned at 2.3x the rate of on-time deliveries. Conducted deep-dive EDA using Matplotlib/Seaborn and recommended logistics improvements projected to reduce churn by 15%; presented findings via stakeholder-ready charts.
View ProjectInsurance Cross-Selling Strategy Analysis
January 1, 2026 – Present
Cleaned and explored a 100K+ record health insurance dataset using Pandas — handled null values, removed duplicates, and standardized column formats before analysis. Segmented customers by age, vehicle ownership, and premium history; identified the 30-45 age group as the highest-conversion segment with a 35% higher positive response rate for vehicle insurance. Recommended a targeted marketing strategy using Seaborn visualizations (heatmaps, bar charts) projected to reduce customer acquisition costs by ~20%.
View ProjectData Analyst (Excel, SQL, Python, Power BI)
Naresh IT
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects demonstrate a strong alignment with the target role of Data Analyst, covering diverse domains like e-commerce, insurance, and streaming. The breadth of skills across SQL, Python, and Power BI indicates adaptability and a willingness to learn and apply various tools. The personal nature of the projects suggests self-motivation and initiative, which are positive indicators for cultural fit in a team that values proactive contributions.
Soft Skills & Operational Fit
The candidate's resume highlights soft skills such as Business Communication, Analytical Thinking, Problem Solving, and Attention to Detail, which are crucial for a Data Analyst role. The project descriptions indicate an ability to translate business requirements into actionable insights and present findings effectively. The focus on improving business metrics (e.g., reducing churn, identifying service quality issues, reducing acquisition costs) suggests a results-oriented approach.