<?xml version="1.0" encoding="UTF-8"?><rss xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:atom="http://www.w3.org/2005/Atom" version="2.0"><channel><title><![CDATA[Pritiportfoliowebsite]]></title><description><![CDATA[Pritiportfoliowebsit]]></description><link>https://pritydabhi.wixsite.com/pritiportfoliowebsit/home</link><generator>RSS for Node</generator><lastBuildDate>Wed, 22 Apr 2026 20:50:38 GMT</lastBuildDate><atom:link href="https://pritydabhi.wixsite.com/pritiportfoliowebsit/blog-feed.xml" rel="self" type="application/rss+xml"/><item><title><![CDATA[American Airways Dashboard]]></title><description><![CDATA[ American Airlines Performance Analysis Problem: Airline companies need to monitor flight performance, delays, and operational efficiency to improve customer experience. Tools Used: Tableau Approach Analyzed airline dataset to evaluate performance metrics Built interactive dashboard to track delays, cancellations, and trends Visualized key KPIs for better decision-making Key Insights Identified patterns in flight delays across time and routes Highlighted factors contributing to operational...]]></description><link>https://pritydabhi.wixsite.com/pritiportfoliowebsit/post/american-airways-dashboard</link><guid isPermaLink="false">68ea02c715335a80a82ebbea</guid><pubDate>Sat, 11 Oct 2025 07:12:57 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/aef016_4779ccc0db914da680f3df1a11676533~mv2.jpg/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>pritydabhi02</dc:creator></item><item><title><![CDATA[Exploratory Retail Data Analysis]]></title><description><![CDATA[ Retail Data Analysis Problem: Businesses struggle to understand sales performance and customer behavior from large transactional datasets. Tools Used: SQL (MySQL) Approach Imported and cleaned raw retail dataset using SQL Performed revenue, product, and customer analysis using aggregation queries Identified trends and patterns through exploratory analysis Key Insights Top countries contributed the majority of revenue Monthly sales trends revealed seasonality and peak periods Best-selling...]]></description><link>https://pritydabhi.wixsite.com/pritiportfoliowebsit/post/exploratory-retail-data-analysis</link><guid isPermaLink="false">68ea0065c3363e86faf9a888</guid><pubDate>Sat, 11 Oct 2025 07:05:32 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/aef016_c73f3ebadabb4c9ca97c7611f5f925a1~mv2.jpg/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>pritydabhi02</dc:creator></item><item><title><![CDATA[King county, Washington House Sales Dashboard]]></title><description><![CDATA[  House Sales Analysis (King County, Washington) Problem: Real estate stakeholders need insights into housing prices, trends, and property features to make informed decisions. Tools Used: Tableau Approach Analyzed housing dataset to explore pricing trends Built interactive dashboard to visualize property features and sales patterns Compared factors influencing house prices Key Insights Identified key factors affecting house prices (location, size, etc.) Observed pricing trends across...]]></description><link>https://pritydabhi.wixsite.com/pritiportfoliowebsit/post/king-county-washington-house-sales-dashboard</link><guid isPermaLink="false">68e9fe204bab99a0463e4470</guid><pubDate>Sat, 11 Oct 2025 06:52:13 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/aef016_d992aad148a84967aded77949562caad~mv2.jpg/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>pritydabhi02</dc:creator></item><item><title><![CDATA[Layoff Data Cleaning Project]]></title><description><![CDATA[In this project we walk through the process used for cleaning the raw layoff's data Layoff Data Cleaning &#38; Exploratory Analysis  Problem Companies faced difficulty understanding layoff trends due to inconsistent and unclean data.  Tools Used:- SQL (Window Functions, CTEs)  Approach Cleaned and standardized raw layoff data using SQL Removed duplicates using ROW_NUMBER and handled missing values with self-joins Performed exploratory analysis to identify trends across companies,...]]></description><link>https://pritydabhi.wixsite.com/pritiportfoliowebsit/post/layoff-data-cleaning-project</link><guid isPermaLink="false">68e9fca615335a80a82eaffa</guid><pubDate>Sat, 11 Oct 2025 06:48:03 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/aef016_24dccae94a7e40faa77847236cc14375~mv2.jpg/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>pritydabhi02</dc:creator></item></channel></rss>