Rakesh Kumar

• Data Analysis Internship - Experience Overview
• Duration: 6 months.
• Department: Data Analytics

Key Responsibilities:

• Data Collection and Cleaning: Assist in gathering data from various sources, including databases and external datasets. Perform data cleaning and preprocessing to ensure the accuracy and quality of the data.
• Data Analysis: Use statistical tools and software (e.g., Excel, SQL, Python) to analyze datasets, identify trends, patterns, and correlations. Work on real projects that involve analyzing large datasets to provide actionable insights.
• Data Visualization: Create visually compelling reports, dashboards, and charts using tools like Tableau, Power BI to present data findings to the team and stakeholders.
• Continuous Learning: Stay updated with the latest trends and technologies in data analysis and apply new techniques and tools to improve the quality and efficiency of your work.

Project: Employee and Patient Data Analysis using SQL.

• Objective: Analyzed a healthcare database containing employee and patient records to improve operational efficiency and patient care.
• Key Tasks: Developed complex SQL queries to extract, clean, and analyze employee and patient data.
  Conducted data integrity checks to ensure accuracy and consistency across multiple tables.
  Created summary reports to identify key trends in patient demographics and employee performance metrics.
  Optimized SQL queries to reduce runtime and improve database performance.
• Outcome: Improved data-driven decision-making by providing actionable insights into patient care and resource allocation.

• Imported and exported data between Excel and GIS software (e.g., ArcGIS, QGIS).
• Utilized Excel for data preprocessing before importing into GIS environments.
• Leveraged Excel capabilities to complement GIS analysis workflows.
• Conducted feature extraction and basemap generation, including using ORI for extraction of topographical features by SOI.

• Cleaned and duplicated customer data, transaction records, and product information using Excel functions such as TRIM, CONCATENATE, and VLOOKUP.
• Integrated data from various sources (e.g., CRM systems, e-commerce platforms) into Excel for unified analysis.
• Ensured data accuracy and consistency across multiple e-commerce datasets.