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Spotify Listening Habits Analytics is a project aimed at analyzing personalized Spotify listening habits and music trends. It involves Exploratory Data Analysis (EDA) with Python Pandas, data processing using SQL Server, and creating visualizations with Power BI. The goal is to uncover insights into listening patterns, track popularity, and artist.
This Capstone Project includes an End to End Data Engineering Pipeline right from Ingesting the data from HTTPs server to cleaning and transforming the data in Azure Databricks and finally reporting the data on Power BI Desktop
Creating Power BI dashboards for "Classic Models" to track KPIs using data from MySQL. Scenarios include inventory breakdowns, finance and sales insights, and regional performance analysis. Visualizations feature funnels, column charts, pie charts, and maps. Power BI Desktop is used for its diverse visuals.
Welcome to the Power BI Projects Repository crafted by Tejas. The project utilized Power BI to analyze CSV-based employee data, offering insights into performance and attrition, aimed at enhancing employee retention and satisfaction.
This repository showcases advanced data analysis techniques applied to SHG's booking data, including SQL queries, Power BI visualizations, and comprehensive documentation. Dive into the analytical insights to witness how data-driven strategies can revolutionize the hospitality industry.
This Power BI dashboard analyzes employee attrition, visualizing key metrics such as overall attrition rate, hiring trends, and active employees by department and job role. It includes demographic insights, performance tracking, and detailed attrition analysis by various factors, helping stakeholders manage and reduce employee turnover effectively.
The primary objective of this project is to develop a comprehensive and visually appealing Power BI dashboard that analyzes the medicine sales data for the entire year of 2023 and 2022.