In this repository you can find my Power BI projects:

• Adventure Works 2020 (from Microsoft Learning)

Diabetes Analytics Dashboard – Power BI 🩺📊 This practice dashboard is built for Data Analytics, Data Visualization, and Data Science learning. It provides meaningful insights into diabetes risk factors using interactive visuals and advanced analytics.

🔹 Key Metrics – Total patients, BMI, glucose, blood pressure, and insulin levels. 🔹 Diabetes Risk Segmentation – Categorized into High, Medium, and Low risk groups. 🔹 Trends & Distribution – Glucose vs. Age, BMI categories, and Blood Pressure analysis. 🔹 Correlation Analysis – Exploring the relationships between glucose, BMI, and diabetes risk. 🔹 Gauge & Pie Charts – Visualizing risk percentage, BMI distribution, and glucose levels. 🔹 Interactive Filters & Drilldowns – Allowing deeper exploration of specific patient groups. 🔹 Predictive Insights – Identifying potential risk patterns through visual analytics.

This project helps in understanding data-driven healthcare insights using Power BI. Thanks to Kaggle for the dataset!

Dataset

This dataset was created by mohannad wathik

Released under Apache 2.0

Contents

This project focuses on data mapping, integration, and analysis to support the development and enhancement of six UNCDF operational applications: OrgTraveler, Comms Central, Internal Support Hub, Partnership 360, SmartHR, and TimeTrack. These apps streamline workflows for travel claims, internal support, partnership management, and time tracking within UNCDF.Key Features and Tools:Data Mapping for Salesforce CRM Migration: Structured and mapped data flows to ensure compatibility and seamless migration to Salesforce CRM.Python for Data Cleaning and Transformation: Utilized pandas, numpy, and APIs to clean, preprocess, and transform raw datasets into standardized formats.Power BI Dashboards: Designed interactive dashboards to visualize workflows and monitor performance metrics for decision-making.Collaboration Across Platforms: Integrated Google Collab for code collaboration and Microsoft Excel for data validation and analysis.

Dataset

This dataset was created by AYUSH CHOUDHARY

Contents

I'm excited to share my latest project—an interactive Power BI dashboard that provides a comprehensive analysis of bike sales data from 2019 to 2024!

Key Highlights of the Dashboard:

📈 Sales Trend Analysis: Understand how bike sales have fluctuated over the years, with peaks in specific months that give us clues about seasonal demand. 🏢 Sales by Store Location: See how different cities like New York and Phoenix lead in terms of total sales revenue. 🚴‍♀️ Customer Demographics: Almost equal contributions from male and female customers—showing the broad appeal of our products. 💳 Payment Method Preferences: Breakdown of the most used payment methods, with insights that can help improve our customer experience. 📊 Revenue by Bike Model: A detailed look at which bike models drive the most revenue, helping guide product focus and inventory management. This dashboard was built to provide actionable insights into the sales performance and customer behavior of a large dataset of 100K records. It highlights the power of data visualization in turning numbers into strategic insights!

Why Power BI? Power BI's flexibility and interactive capabilities made it the ideal tool for visualizing the data, allowing users to drill down into specific details using slicers for bike models and time periods. 💡

Would love to hear your thoughts or any feedback on this project! If you’re interested in how this dashboard was built or want to discuss data visualization, feel free to reach out. Let’s transform data into stories that drive success! 🌟

China CDB: Number of Medium Size Project Loans: BI: Energy: Electricity: R data was reported at 7.000 Unit in 2002. This records an increase from the previous number of 6.000 Unit for 2001. China CDB: Number of Medium Size Project Loans: BI: Energy: Electricity: R data is updated yearly, averaging 6.000 Unit from Dec 2000 (Median) to 2002, with 3 observations. The data reached an all-time high of 7.000 Unit in 2002 and a record low of 4.000 Unit in 2000. China CDB: Number of Medium Size Project Loans: BI: Energy: Electricity: R data remains active status in CEIC and is reported by The People's Bank of China. The data is categorized under Global Database’s China – Table CN.KE: China Development Bank (CDB): Loan.

This is the filtered dataset of LA Census Tracts from the 500 Cities project 2017 release. This dataset includes 2015, 2014 model-based small area estimates for 27 measures of chronic disease related to unhealthy behaviors (5), health outcomes (13), and use of preventive services (9). Data were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. The project was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. It represents a first-of-its kind effort to release information on a large scale for cities and for small areas within those cities. It includes estimates for the 500 largest US cities and approximately 28,000 census tracts within these cities. These estimates can be used to identify emerging health problems and to inform development and implementation of effective, targeted public health prevention activities. Because the small area model cannot detect effects due to local interventions, users are cautioned against using these estimates for program or policy evaluations. Data sources used to generate these measures include Behavioral Risk Factor Surveillance System (BRFSS) data (2015, 2014), Census Bureau 2010 census population data, and American Community Survey (ACS) 2011-2015, 2010-2014 estimates. Because some questions are only asked every other year in the BRFSS, there are 7 measures from the 2014 BRFSS that are the same in the 2017 release as the previous 2016 release. More information about the methodology can be found at www.cdc.gov/500cities.

Global Revenue & Customer Insights with Power BI

Just wrapped up an interactive Power BI Dashboard analyzing 2011 retail data! This project highlights key trends in global revenue, demand, and customer behavior.

🔎 Key Insights: ✅ Monthly Revenue Trends 📉 ✅ Country-Wise Demand 🌍 ✅ Customer Revenue Segmentation 🛒 ✅ Seasonal Analysis with Filters 🌸❄

💡 Skills Applied: 🔹 Power BI for Data Visualization 🔹 DAX for Advanced Calculations 🔹 Data Transformation with Power Query 🔹 Data Storytelling for Business Insights

🚀 Business Impact: ✔ Identify growth opportunities ✔ Understand customer preferences ✔ Optimize sales strategies

In this report, i will be analyzing the major multinational companies across Brasil using several some economic and company performance indicators by year and by month from 2016 to 2018.

Average Review Performance by product category in compares to the Total revenues. All these reveals some interesting insights.

A data dashboard in the form of a document link to Microsoft Power BI Dashboard of the same name, prepared and maintained by the Department of Economic Prosperity and Housing. Data is updated quarterly.NOTE: This product and the information shown is provided "AS IS" and exists for informational purposes only. The City of Vancouver (COV) makes no warranties regarding the accuracy of such data. This product and information is not prepared, nor is suitable, for legal, engineering, or surveying purposes. Any sale, reproduction or distribution of this information, or products derived therefrom, in any format is expressly prohibited. Data are provided by multiple sources and subject to change without notice.

China CDB: Number of Medium Size Project Loans: BI: Energy: Electricity: U data was reported at 15.000 Unit in 2002. This records a decrease from the previous number of 37.000 Unit for 2001. China CDB: Number of Medium Size Project Loans: BI: Energy: Electricity: U data is updated yearly, averaging 37.000 Unit from Dec 2000 (Median) to 2002, with 3 observations. The data reached an all-time high of 65.000 Unit in 2000 and a record low of 15.000 Unit in 2002. China CDB: Number of Medium Size Project Loans: BI: Energy: Electricity: U data remains active status in CEIC and is reported by The People's Bank of China. The data is categorized under Global Database’s China – Table CN.KE: China Development Bank (CDB): Loan.

China CDB: Medium Size Project Loans: BI: Energy: Electricity: Urban data was reported at 4.522 RMB bn in 2002. This records a decrease from the previous number of 13.226 RMB bn for 2001. China CDB: Medium Size Project Loans: BI: Energy: Electricity: Urban data is updated yearly, averaging 11.244 RMB bn from Dec 2000 (Median) to 2002, with 3 observations. The data reached an all-time high of 13.226 RMB bn in 2001 and a record low of 4.522 RMB bn in 2002. China CDB: Medium Size Project Loans: BI: Energy: Electricity: Urban data remains active status in CEIC and is reported by The People's Bank of China. The data is categorized under Global Database’s China – Table CN.KE: China Development Bank (CDB): Loan.

🌿 Green Tea Sales Analysis Dashboard I’m excited to share my latest Power BI project — a dynamic and interactive dashboard designed to analyze Green Tea sales data. This comprehensive solution offers actionable insights into key metrics such as revenue, product performance, customer behavior, and geographical distribution. With this dashboard, stakeholders can easily monitor sales trends, compare year-over-year performance, and make data-driven decisions.

🖥️ Key Dashboard Features Net Revenue & Total Bills Generated: Provides a clear view of overall financial performance.

Salesman Experience Analysis: Visualizes the average experience of sales representatives and its impact on sales.

Geographical Sales Distribution: An interactive map highlights sales performance across different regions.

Customer Type Breakdown: A detailed pie chart categorizes customers into Retail, Institutional, and Online segments.

Product Performance: A combination of treemap and bar chart visualizations showcase top-selling and underperforming products.

Revenue Trend & Discount Analysis: Year-over-year revenue and discount trends are analyzed to identify patterns and anomalies.

Date & Quarter Filters: Users can filter data using interactive controls for year, month, or quarter-based analysis.

📊 Dataset Overview The dataset used for this analysis contains essential information, including:

Sales Date

Total Sales Revenue

Product Category

Sales Volume (Tons)

Customer Type

Region & Country

Salesman Experience (Years)

🛠️ Tools Used Power BI – For data visualization and dashboard development

DAX (Data Analysis Expressions) – For complex calculations and dynamic data representation

Soluções completas em análise de dados: estruturação, governança, visualização e preditiva com Power BI, SQL e Python.

Completed a job simulation where I strengthened my PowerBI skills to better understand clients and their data visualisation needs. Demonstrated expertise in data visualization through the creation of Power BI dashboards that effectively conveyed KPIs, showcasing the ability to respond to client requests with well-designed solutions. Strong communication skills reflected in the concise and informative email communication with engagement partners, delivering valuable insights and actionable suggestions based on data analysis. Leveraged analytical problem-solving skills to examine HR data, particularly focusing on gender-related KPIs, and identified root causes for gender balance issues at the executive management level, highlighting a commitment to data-driven decision-making.

McKinsey Solve Global Assessment Dataset (2018–2025)

🧠 Context

McKinsey's Solve is a gamified problem-solving assessment used globally in the consulting firm’s recruitment process. This dataset simulates assessment results across geographies, education levels, and roles over a 7-year period. It aims to provide deep insights into performance trends, candidate readiness, resume quality, and cognitive task outcomes.

📌 Inspiration & Purpose

Inspired by McKinsey’s real-world assessment framework, this dataset was designed to enable: - Exploratory Data Analysis (EDA) - Recruitment trend analysis - Gamified performance modelling - Dashboard development in Excel / Power BI - Resume and education impact evaluation - Regional performance benchmarking - Data storytelling for portfolio projects

Whether you're building dashboards or training models, this dataset offers practical and relatable data for HR analytics and consulting use cases.

🔍 Dataset Source

• Data generated by Oluwademilade Adeniyi (Demibolt) with the assistance of ChatGPT by OpenAI Structure and logic inspired by McKinsey’s public-facing Solve information, including role categories, game types (Ecosystem, Redrock, Seawolf), education tiers, and global office locations The entire dataset is synthetic and designed for analytical learning, ethical use, and professional development

🧾 Dataset Structure

This dataset includes 4,000 rows and the following columns: - Testtaker ID: Unique identifier - Country / Region: Geographic segmentation - Gender / Age: Demographics - Year: Assessment year (2018–2025) - Highest Level of Education: From high school to PhD / MBA - School or University Attended: Mapped to country and education level - First-generation University Student: Yes/No - Employment Status: Student, Employed, Unemployed - Role Applied For and Department / Interest: Business/tech disciplines - Past Test Taker: Indicates repeat attempts - Prepared with Online Materials: Indicates test prep involvement - Desired Office Location: Mapped to McKinsey's international offices - Ecosystem / Redrock / Seawolf (%): Game performance scores - Time Spent on Each Game (mins) - Total Product Score: Average of the 3 game scores - Process Score: A secondary assessment component - Resume Score: Scored based on education prestige, role fit, and clarity - Total Assessment Score (%): Final decision metric - Status (Pass/Fail): Based on total score ≥ 75%

✅ Why Use This Dataset

• Benchmark educational and regional trends in global assessments
• Build KPI cards, donut charts, histograms, or speedometer visuals
• Train pass/fail classifiers or regression models
• Segment job applicants by role, location, or game behaviour
• Showcase portfolio skills across Excel, SQL, Power BI, Python, or R
• Test dashboards or predictive logic in a business-relevant scenario

💡 Credit & Collaboration

• Data Creator: Oluwademilade Adeniyi (Me) (LinkedIn, Twitter, GitHub, Medium)
• Collaborator: ChatGPT by OpenAI
• Inspired by: McKinsey & Company’s Solve Assessment

China CDB: Number of Medium Size Project Loans: BI: Energy: Electricity data was reported at 157.000 Unit in 2002. This records an increase from the previous number of 120.000 Unit for 2001. China CDB: Number of Medium Size Project Loans: BI: Energy: Electricity data is updated yearly, averaging 151.000 Unit from Dec 1997 (Median) to 2002, with 5 observations. The data reached an all-time high of 165.000 Unit in 1998 and a record low of 104.000 Unit in 1997. China CDB: Number of Medium Size Project Loans: BI: Energy: Electricity data remains active status in CEIC and is reported by The People's Bank of China. The data is categorized under Global Database’s China – Table CN.KE: China Development Bank (CDB): Loan.

This is a realistic and structured pizza sales dataset covering the time span from **2024 to 2025. ** Whether you're a beginner in data science, a student working on a machine learning project, or an experienced analyst looking to test out time series forecasting and dashboard building, this dataset is for you.

📁 What’s Inside? The dataset contains rich details from a pizza business including:

✅ Order Dates & Times ✅ Pizza Names & Categories (Veg, Non-Veg, Classic, Gourmet, etc.) ✅ Sizes (Small, Medium, Large, XL) ✅ Prices ✅ Order Quantities ✅ Customer Preferences & Trends

It is neatly organized in Excel format and easy to use with tools like Python (Pandas), Power BI, Excel, or Tableau.

💡** Why Use This Dataset?** This dataset is ideal for:

📈 Sales Analysis & Reporting 🧠 Machine Learning Models (demand forecasting, recommendations) 📅 Time Series Forecasting 📊 Data Visualization Projects 🍽️ Customer Behavior Analysis 🛒 Market Basket Analysis 📦 Inventory Management Simulations

🧠 Perfect For: Data Science Beginners & Learners BI Developers & Dashboard Designers MBA Students (Marketing, Retail, Operations) Hackathons & Case Study Competitions

pizza, sales data, excel dataset, retail analysis, data visualization, business intelligence, forecasting, time series, customer insights, machine learning, pandas, beginner friendly

This dataset contains 10,000 synthetic records simulating the migratory behavior of various bird species across global regions. Each entry represents a single bird tagged with a tracking device and includes detailed information such as flight distance, speed, altitude, weather conditions, tagging information, and migration outcomes.

The data was entirely synthetically generated using randomized yet realistic values based on known ranges from ornithological studies. It is ideal for practicing data analysis and visualization techniques without privacy concerns or real-world data access restrictions. Because it’s artificial, the dataset can be freely used in education, portfolio projects, demo dashboards, machine learning pipelines, or business intelligence training.

With over 40 columns, this dataset supports a wide array of analysis types. Analysts can explore questions like “Do certain species migrate in larger flocks?”, “How does weather impact nesting success?”, or “What conditions lead to migration interruptions?”. Users can also perform geospatial mapping of start and end locations, cluster birds by behavior, or build time series models based on migration months and environmental factors.

For data visualization, tools like Power BI, Python (Matplotlib/Seaborn/Plotly), or Excel can be used to create insightful dashboards and interactive charts.

Join the Fabric Community DataViz Contest | May 2025: https://community.fabric.microsoft.com/t5/Power-BI-Community-Blog/%EF%B8%8F-Fabric-Community-DataViz-Contest-May-2025/ba-p/4668560