As part of my hands-on journey into data analytics, I worked on real-world datasets and applied analytical techniques to extract actionable insights using the following tools and methods: • 🔹 Excel: Performed data cleaning, trend analysis, and reporting using advanced functions (VLOOKUP, COUNTIFS, PivotTables, Conditional Formatting). • 🔹 EDA (Exploratory Data Analysis): Identified patterns, outliers, and relationships in data to support better decision-making. • 🔹 ETL Concepts: Practiced data extraction, transformation, and loading techniques across multiple tools to build clean, analysis-ready datasets. • 🔹 Power BI: Created interactive dashboards and visual reports; utilized filters, slicers, and basic DAX functions to enhance data storytelling. • 🔹 Python: Used libraries like Pandas, NumPy, and Matplotlib to automate data preparation and visualize trends. • 🔹 MySQL: Wrote basic to intermediate queries for data retrieval, filtering, joins, and aggregations from relational databases. Throughout this experience, I built a strong foundation in data analytics and developed a problem-solving mindset by working across tools and technologies in a structured, project-based learning approach.