Aspiring Data Analyst with a strong foundation in data analysis, data visualization, SQL, Excel, Python, and Power BI. Recently completed professional training in Data Analytics and developed hands-on experience through …
Aspiring Data Analyst with a strong foundation in data analysis, data visualization, SQL, Excel, Python, and Power BI. Recently completed professional training in Data Analytics and developed hands-on experience through academic and practice projects involving data cleaning, transformation, analysis, and dashboard creation. Passionate about converting raw data into meaningful insights that support business decision-making and improve operational efficiency.
Proficient in Microsoft Excel, including Pivot Tables, Pivot Charts, Lookup functions, Conditional Formatting, Data Validation, and advanced formulas for analyzing and organizing large datasets. Skilled in SQL for writing queries involving joins, subqueries, aggregate functions, window functions, Common Table Expressions (CTEs), and database management. Comfortable extracting, cleaning, and manipulating data to generate accurate reports and actionable insights.
Knowledgeable in Python for data analysis using Pandas, NumPy, Matplotlib, and basic data visualization techniques. Experienced in data preprocessing, handling missing values, removing duplicates, formatting datasets, performing exploratory data analysis (EDA), and generating visual reports. Familiar with creating line charts, bar charts, pie charts, and trend analysis to identify business patterns.
Hands-on experience in Power BI, creating interactive dashboards, KPIs, DAX measures, calculated columns, slicers, drill-through reports, and data modeling. Capable of designing visually appealing dashboards that help stakeholders monitor business performance and make data-driven decisions. Familiar with importing data from multiple sources, transforming data using Power Query, and building relationships between tables.
Completed multiple practice projects such as Superstore Sales Analysis and Hospital Management Analysis. These projects involved analyzing sales trends, customer behavior, department performance, patient visits, billing analysis, treatment.
<p>Developed an end-to-end data analytics project to analyze hospital operations and patient data using Excel, SQL, Power BI, and Python. The project focused on improving operational efficiency by analyzing patient admissions, department performance, billing, treatment costs, length of stay, and payment methods. Performed data cleaning, transformation, and exploratory data analysis to identify trends and generate actionable insights. Designed interactive dashboards to visualize key performance indicators (KPIs) such as patient volume, department-wise admissions, monthly patient visits, revenue, average length of stay, and payment mode distribution. The analysis supported data-driven decision-making to enhance hospital resource utilization and patient care.</p>
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