Transforming raw data into actionable insights through Python, SQL, and Visualization.
> import pandas as pd
> import matplotlib.pyplot as plt
> df = pd.read_csv('insights.csv')
> df.analyze()
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DEPI
NTI
Google Data Analytics – Foundations Certificate I successfully completed the Foundations: Data, Data, Everywhere course, part of the Google Data Analytics Professional Certificate program offered through Google and Coursera. This course provided a strong introduction to the field of data analytics, focusing on the core concepts and processes used by data analysts in real-world scenarios. It covered the fundamentals of the data analysis lifecycle, including asking the right questions, preparing and cleaning data, processing and analyzing datasets, and effectively sharing insights. Throughout the course, I gained knowledge in: The data analysis process and problem-solving mindset Types of data and data structures Data-driven decision-making Basic data ethics and data integrity principles Introduction to tools commonly used in analytics This certificate represents my foundational step into data analysis and supports my ability to approach data problems with a structured and analytical mindset.
View Certificate ↗Excel Data Analysis – Lookup Functions Project I successfully completed the How to Use Lookup Reference Math and Text Functions in Excel project through Coursera. This hands-on project focused on mastering essential Excel functions used in data analysis, particularly lookup and reference functions that are widely used to retrieve and manipulate data efficiently. During this project, I developed practical skills in: Using advanced lookup functions such as VLOOKUP and other reference tools Applying text and mathematical functions to clean and transform data Organizing datasets for better usability and analysis Improving accuracy and efficiency in handling large datasets This project strengthened my Excel skills and enhanced my ability to work with structured data, making it easier to extract insights and support data-driven decisions.
View Certificate ↗Data Analysis Diploma – AMIT Learning I completed a comprehensive Data Analysis Diploma at AMIT Learning, where I gained practical and theoretical knowledge covering the full data analysis lifecycle. Throughout the program, I developed hands-on experience in: Data cleaning, preprocessing, and transformation Exploratory Data Analysis (EDA) and data interpretation Working with tools such as Excel, Python (Pandas, NumPy), and data visualization libraries Creating dashboards and visual reports using Tableau Applying statistical concepts to support data-driven decision-making The diploma emphasized real-world projects, allowing me to analyze datasets, extract insights, and present findings in a clear and impactful way. This program strengthened my ability to turn raw data into actionable insights and prepared me for solving real business problems using data analysis techniques.
Google Data Analytics – Ask Questions to Make Data-Driven Decisions Certificate I successfully completed the Ask Questions to Make Data-Driven Decisions course, part of the Google Data Analytics Professional Certificate program offered through Google and Coursera. This course deepened my understanding of the analytical problem-solving process, focusing on how to ask effective questions to guide data-driven decision-making. It covered essential techniques for structuring business problems, communicating with stakeholders, and clearly defining the data needed to find actionable answers. Throughout the course, I gained knowledge in: Applying structured thinking frameworks to solve complex business problems Crafting SMART (Specific, Measurable, Action-oriented, Relevant, Time-bound) questions Understanding and communicating effectively with business stakeholders Defining clear data requirements and establishing key performance metrics Distinguishing between qualitative and quantitative data approaches This certificate strengthens my ability to bridge the gap between business objectives and data analysis, ensuring that analytical projects are guided by clear, purposeful questions from the very start.
View Certificate ↗Oasis Infobyte – Data Analytics Internship Certificate I successfully completed a one-month AICTE OIB-SIP internship in Data Analytics with Oasis Infobyte, receiving wonderful remarks for my performance. This hands-on internship provided practical experience in the field of data analytics, allowing me to apply core analytical concepts to real-world datasets. It bridged the gap between theoretical knowledge and professional application through rigorous, project-based learning. Throughout the internship, I gained practical experience in: * Performing data cleaning and preprocessing to ensure data accuracy and integrity * Conducting exploratory data analysis (EDA) to uncover underlying trends and patterns * Developing clear and impactful data visualizations to communicate complex insights * Applying analytical problem-solving frameworks to real-world data challenges * Translating raw data into actionable takeaways for business use This certificate represents my hands-on capability in data analysis and reinforces my readiness to tackle practical data challenges with a structured and execution-focused approach.
Self-Employed / Remote
Global Energy Analysis Project This project provides a comprehensive analysis of energy production, consumption, and trends across the world. Using real-world datasets, I explored how different countries generate and use energy, with a focus on renewable vs non-renewable sources, efficiency, and sustainability patterns. The project includes data cleaning, transformation, and visualization to uncover key insights such as: Global energy consumption trends over time Comparison between renewable and fossil fuel usage Country-level energy performance and dependencies Identification of leading nations in clean energy adoption I used data analysis and visualization tools (such as Excel/Tableau/Python – adjust based on what you used) to create interactive dashboards and clear visual storytelling. These insights help highlight the global shift toward sustainable energy and support data-driven decision-making.
View Project ↗UK Train Data Analysis Project This project focuses on analyzing railway operations in the UK to uncover insights related to journey performance, delays, and customer behavior. The goal was to transform raw transportation data into meaningful insights that can support better decision-making and improve service efficiency. I followed a structured data analysis process starting with defining key business questions, then preparing and cleaning the dataset by handling missing values, standardizing formats, and ensuring data consistency. Special attention was given to time-based data, where datetime transformations and corrections were applied to accurately calculate journey durations and delays. Using Python (Pandas, NumPy, Matplotlib, Seaborn) in Jupyter Notebook, I performed data exploration and feature engineering, creating new variables such as: Journey Duration Delay Duration Day of the Week (Journey & Purchase) Time Period Categories (Morning, Afternoon, Evening, Night) Route combinations between stations The analysis revealed patterns in: Most active stations and routes Delay frequency and main causes (e.g., signal failures, weather, staffing) Customer behavior in ticket purchases and payment methods Distribution of ticket types, classes, and refund requests Visualizations were created using both Python and Tableau to present insights clearly and interactively. Finally, the results were summarized in a PowerPoint presentation to communicate findings in a simple and impactful way. This project demonstrates my ability to clean complex datasets, handle time-series data, perform feature engineering, and deliver actionable insights through data visualization.
View Project ↗I am available for freelance projects and internships. Let's discuss how data can help your business grow.