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Data Analyst with less than a year in SQL, Power BI & Excel
Motivated and detail-oriented data analyst with a Bachelor of Technology in Electrical Engineering (CSVTU) and ongoing training in Data Science and Data Analytics at UpGrad Learning Centre. Hands-on experience across the full analytics stack - from designing relational databases and writing multi-table SQL queries to building interactive Power BI dashboards and Excel-based reporting systems. Completed real-world, end-to-end projects covering database design, data cleaning, joins and CTEs, KPI dashboard design, and business insight generation using MySQL, Power BI, Excel, and Tableau. Strong written and oral English communication, a proactive mindset, and sharp attention to detail. Quick learner who prioritises tasks effectively and performs well under tight deadlines. Open to fresher and up to 1 year experience roles in data and analytics.
UpGrad Learning Centre
Data Science and Data Analytics (Training)
N/A – June 30, 2026
Jawahar Navodaya Vidyalaya
Higher Secondary Education · Science (PCM)
N/A – May 31, 2021
Chhattisgarh Swami Vivekanand Technology University (CSVTU)
Bachelor of Technology · Electrical Engineering
N/A – June 30, 2025
Locoshed Railway
Industrial Intern
January 1, 2024 – December 31, 2024
Bilāspur, Chhattisgarh, India
Student Performance Analysis Dashboard
June 25, 2026 – Present
Analysed a dataset of 1,000 students across 10 variables including attendance rate, study hours, parental support, extracurricular activities, previous grades, and final grades. Applied advanced Excel formulas - VLOOKUP, XLOOKUP, IF/IFS, SUMIF, COUNTIF, AVERAGEIF, and Array Formulas to calculate grade classifications (A1, A2, B1, etc.) and performance remarks for all 1,000 records. Built Pivot Tables to analyse the impact of parental support level, gender, and online class attendance on average final grade; created a Parent Support Pivot showing distribution across High (345), Medium (350), and Low (305) categories. Developed a Summary Sheet with key metrics (average, max, min final grades) and an Attendance vs Final Grade analysis revealing how attendance rate correlates with student outcomes. Designed an interactive Dashboard with slicers and dynamic charts (bar, line, pie) to visualise grade distributions, gender comparisons, and attendance trends enabling quick data-driven insights for educators. Performed end-to-end data cleaning and validation - handled missing values, standardised grade formats, removed inconsistencies, and ensured data integrity across all sheets.
View ProjectOlist E-Commerce Database Design & SQL Analysis
June 25, 2026 – Present
Designed and built a normalised relational database from 9 raw CSV datasets (customers, orders, order items, products, sellers, payments, reviews, geolocation, category translation) covering 100,000+ real e-commerce orders. Cleaned and standardised messy real-world data using NULLIF, COALESCE, TRIM/REPLACE and type casting to fix blank dates, inconsistent state codes, and missing category values across all 9 tables. Created Primary Keys, Foreign Keys, and composite keys to enforce referential integrity across linked tables, and validated relationships using anti-join checks (e.g. detecting orphaned seller records). Wrote multi-table JOIN queries and CTEs to calculate total revenue, average order value, top 10 categories by revenue, and month-over-month sales trends. Built a delivery performance model using DATEDIFF and CASE logic to flag late vs. on-time deliveries by state, segmented customers by loyalty (One-time / Returned-once / Loyal 3+), and linked delivery speed to review scores finding that faster deliveries correlate with higher satisfaction. Created reusable SQL Views (v_delivery_performance, v_sales_by_category) and a consolidated 6-table export dataset, which was used directly as the data source for the Power BI dashboard below.
View ProjectE-Commerce Sales, Delivery & Customer Analytics Dashboard
June 25, 2026 – Present
Designed an interactive Power BI dashboard on top of the curated SQL dataset above, turning a 100,000+ row relational database into a single decision-ready report for business stakeholders. Built 4 KPI cards - Total Revenue, Total Orders, Total Customers, and Average Order Value - for an instant snapshot of business performance. Created a year-over-year, month-wise revenue trend line chart to track seasonality, alongside a category-wise bar chart highlighting top revenue-generating product categories. Visualised payment-method revenue share, order-status distribution, and state-wise revenue using donut and clustered bar charts, plus a year slicer for dynamic, self-service filtering by non-technical stakeholders. Demonstrated the full BI workflow end-to-end - from raw CSVs, to a cleaned MySQL database, to a polished, interactive Power BI report.
View ProjectCultural Fit Analysis
The candidate's project diversity, covering Excel, SQL, and Power BI, indicates a broad interest in data analytics tools and methodologies. The ongoing Data Science and Data Analytics training at UpGrad, alongside a Bachelor's in Electrical Engineering, shows a commitment to continuous learning and a structured approach to skill development. The personal projects are well-documented and demonstrate initiative, which aligns with a proactive and growth-oriented culture. The candidate is a fresher, and the projects show a strong drive to gain practical experience, which is a good cultural fit for roles that value self-starters.
Soft Skills & Operational Fit
The candidate demonstrates strong soft skills such as attention to detail, proactive mindset, fast learning, task prioritization, and teamwork, which are crucial for operational fit in a data analyst role. The project descriptions are clear and well-structured, indicating good communication and report writing abilities. The industrial internship, though not directly data-related, shows exposure to professional environments and process analysis.