In this project, I utilized Python to conduct an Exploratory Data Analysis (EDA) in order to reveal trends, extract valuable insights, and address pertinent business inquiries.

The business management has requested insights into the sales performance across products and customers. This data analysis project centers on examining sales and customer data from Adventure Works stores. The objective is to discover insights, identify trends, and determine key performance indicators to address business inquiries

 This data analysis project explores the interplay between customer occupations and purchasing behaviors from 2015 to 2017 within the Adventure Works business. Through rigorous data examination and advanced analytics, it aims to unearth actionable insights for refining business strategies and elevating customer engagement

In this analysis, we leveraged the power of Power BI to gain valuable insights and extract meaningful information from various datasets related to lead management and sales performance. The analysis focused on providing a comprehensive view of the lead journey, team performance, Lead source performance and watched demo report. 

This data analysis project focuses on analyzing sales data from the Urban Essential Stores located in different shopping malls in Turkey. The project aims to uncover insights, trends, and key performance indicators to inform business decisions. The dataset includes information on revenue, quantities sold, categories, age, gender, and payment methods. 

The objective of this project is to analyze the Adidas sales database for the year 2020 and 2021 and identify key insights to help improve sales performance and optimize business strategies. By analyzing the sales data, we aim to understand factors influencing sales, identify trends, and uncover opportunities for growth. The analysis will be conducted using Excel to provide an interactive and insightful dashboard.

In this project, I utilized Python to conduct an in-depth analysis of QuickMart sales data. Through this analysis, I gained valuable insights and a comprehensive overview of the supermarket's activities, enabling me to make informed recommendations and strategic decisions.

This data analysis project focuses on analyzing sales performance using SQL Server and visualizing the insights using Power BI. The project aims to provide valuable insights into sales trends, performance metrics, key factors impacting revenue generation and answer Business Questions.

 In this project, I conducted a comprehensive analysis of historical data from Walmart stores. By exploring the data, I aimed to answer key business questions and provide valuable recommendations based on the insights derived from the analysis.

The purpose of this project is to comprehensively understand the business flow by analyzing sales performance across different states, various times of the day, and the performance of different delivery agents. By exploring these factors, valuable insights can be gained to optimize business operations and drive growth.

In this project, I conducted an analysis of Pizza Sales data with the objective of answering key business questions and gaining valuable insights. By exploring the data, patterns and trends in pizza sales were identified, enabling informed decision-making and potential improvements in sales strategies.

The primary objective of this project was to analyze and understand the impact of COVID-19 on various regions and countries worldwide. Through data analysis and exploration, we aimed to gain insights into the spread of the virus, its effects on different populations, healthcare systems, and economies. The findings from this project can contribute to a better understanding of the pandemic and support decision-making processes for public health and policy interventions.

In this project, I utilized SQL to clean and preprocess a housing dataset. By applying various data cleaning techniques such as handling missing values, removing duplicates, correcting data inconsistencies, and transforming data formats, I ensured the dataset was prepared for further analysis and modeling. The cleaned dataset can now be used to derive meaningful insights and build predictive models for housing-related analysis.

In this project, I performed data cleaning, manipulation, and modeling in Excel. This involved utilizing VLOOKUP to merge datasets, creating new date columns with text and date functions, standardizing columns, and formatting data. Additionally, I aggregated the dataset into tables using pivot tables and used them to build a dashboard.