Vikram Singh Padiyar

Data Analyst with a strong record at AI Variant, utilizing advanced Excel and SQL skills to identify critical success factors in crowdfunding projects. Proficient in data visualization and storytelling, creating impactful dashboards that facilitate informed decision-making for stakeholders. Demonstrates exceptional problem-solving skills and effective collaboration within teams.

• Date of Birth: 06/05/99
• Gender: Male
• Marital Status: Single/Unmarried

• English
• Hindi

Appointed as captain of the school scout team. Participated in the National Service Scheme in school and received a B certificate. 

• Cricket
• Travelling

Crowdfunding project: Excel, SQL, Tableau, Power BI, basic Python, to analyze crowdfunding projects and determine key success factors, trends, and performance metrics using data analytics techniques, crowdfunding platforms need insights into project success rates, funding patterns, and backer behavior, understanding these trends helps businesses optimize project strategies, attract more backers, and set realistic goals, successfully converted Epoch time into a natural date format, enabling accurate time-based analysis, built a Calendar Table with detailed time attributes, allowing businesses to analyze project trends over different time periods (year, month, quarter, financial year, etc.), designed a data model that improved the efficiency of analyzing crowdfunding projects by linking multiple datasets, provided KPI insights on project performance, helping stakeholders track the total number of projects by outcome, location, category, and time, identified top-performing projects based on backers and funds raised, allowing businesses to replicate success strategies, analyzed successful projects to determine the average duration, amount raised, and number of backers, improving project planning, calculated success rates by category, year, month, and funding goals, giving businesses a data-driven approach to optimize their campaigns, created interactive dashboards in Power BI and Tableau, making data-driven decision-making easier for stakeholders

Manufacturing data analytics (report analytics and dashboard) to analyze manufacturing performance data and identify patterns in rejection and wastage to improve product quality and operational efficiency, analyzed key production KPIs: manufacture qty, rejected qty, processed qty, and wastage qty using SQL and Excel, built interactive dashboards in Power BI and Tableau to track employee-wise and machine-wise rejected qty, production trends, and manufacture vs rejected qty, department-wise rejection comparison, identified rejection patterns, reducing manual analysis time and helping improve production efficiency, automated reporting tools to support real-time data-driven decisions in manufacturing operations

Internship: 6 months

Haldawani ,Uttarakhand