Forem: Bakare sukurat Aderonke

Analyzing Hospital Emergency Room Records with Power BI

Bakare sukurat Aderonke — Fri, 28 Feb 2025 09:21:05 +0000

Healthcare data holds incredible insights, and as a data analyst, I love transforming raw numbers into meaningful stories. This time, I worked on an Emergency Room (ER) Visit Analysis to uncover key trends in patient visits, satisfaction, and service efficiency.

Project Overview

I got this dataset from a data scientist running a 20-day data challenge on Instagram. At first, I explored it independently, but later, I introduced it to my community during a challenge, and everyone found it interesting. That’s when we all decided to work on it together and share our dashboards. After numerous breaks and pauses, I finally put together this visualization, and I’m excited to showcase my insights!

Tools Used

Excel – Data cleaning and preparation

PowerPoint – Design enhancements for dashboard elements

Power BI – Data visualization and dashboard creation

Key Insights from the Dashboard

Total Patient Visits: The ER recorded 9,216 visits, with a nearly even split between scheduled (49.96%) and non-scheduled (50.04%) appointments.

Patient Satisfaction: The average satisfaction score stands at 5.47, but a concerning 75.10% of services remain unrated.

Waiting Time: Patients wait an average of 35.26 minutes before receiving medical attention.

Patient Demographics:
Most patients are adults, followed by middle childhood and teenage groups.

Weekend visits (2.6K) are significantly lower than weekday visits (6.6K).

Department Referrals: While many patients didn’t require further referrals (5,400 cases), some were directed to General Practice, Orthopedics, and other specialties.

Seasonal Trends: The highest number of visits occurred in August (1,024), while February recorded the lowest (431).

Challenges and Learnings

Balancing multiple projects and commitments made it hard to complete this dashboard sooner, but I eventually pushed through.

Presenting insights in a clear and engaging way required creative dashboard design, which PowerPoint helped refine.

Community involvement gave me a fresh perspective and motivated me to finalize my work.

Final Thoughts

This project reinforced my passion for healthcare analytics and storytelling through data. I’m glad I took on this challenge, and I hope it provides valuable insights for understanding ER visits better.

📌 Check out the full project on GitHub: [https://github.com/Aderonke101]

💡 What do you think of these insights? Let’s discuss in the comments!

Unveiling Insights with Excel & PowerPoint – Full Project Now on GitHub!

Bakare sukurat Aderonke — Thu, 16 Jan 2025 09:23:23 +0000

Unveiling Insights with Excel & PowerPoint – Full Project Now on GitHub!

Hey Devs! 👋

I’ve just wrapped up my latest project, [Project Name], and it’s live on GitHub (https://github.com/Aderonke101/Excel-HR_ANALYTICS).

The best part? It’s built entirely with Excel and PowerPoint! 💼

In this project, I’ve leveraged Excel’s powerful data analysis features and PowerPoint’s visual storytelling capabilities to create an interactive Dashboard to present key Insights. The project focuses on Insights into Human Resource Workforce Trends.

Here’s what you’ll find in my repository:

🧑‍💻 Excel Files & PowerPoint Deck: Get access to the raw data and polished visuals.

📊 Interactive Dashboard Combining Powerpoint and Excel: A visual representaion of key metrics and findings.

📖 Comprehensive README: A step-by-step guide to understanding the workflow and methodology.

💡 Key Takeaways: Learn how to create impactful presentations and dashboards with Excel and PowerPoint.

Feel free to check it out and let me know your thoughts – I’m always open to feedback and discussions!

Excel #PowerPoint #DataAnalysis #PortfolioProjects #GitHub

Title: Coffee Sales Order Analysis with Excel: Dashboard, Pivot Table & Insights

Bakare sukurat Aderonke — Tue, 24 Dec 2024 16:26:01 +0000

Introduction:
Hello, Dev community! I’m excited to share my latest project—an Excel-based coffee sales order analysis. This project showcases my data analysis and visualization skills, and it includes a dynamic dashboard, an insightful pivot table, and other components that help turn raw data into actionable insights.

Project Highlights:

Interactive Dashboard: Designed to provide a quick overview of sales trends, top-performing products, and customer insights.

_Pivot Table: _A powerful tool to analyse and summarize large datasets effortlessly.

Data Cleaning & Analysis: Ensured accurate, clean data for effective decision-making.

Actionable Insights: Extracted patterns and trends to aid business strategy.

Screenshots:
Here’s a sneak peek of the project:

GitHub Repository:
The full project, along with a detailed README, is available on my GitHub.
Feel free to explore:
Coffee Sales Order GitHub Repository (https://github.com/Aderonke101/Coffee-Sales-Order-Analysis-Excel)

Why I Created This:
As I transition into tech, I’m focusing on building practical projects that demonstrate my skills in Excel, data analysis, and visual storytelling. This project is a step forward in showcasing what I can bring to the table.

What’s Next:
I’d love to hear your thoughts! Do you have any feedback, suggestions, or ideas for similar projects?

Feel free to connect or leave a comment below.

Thank you for reading!

Title: Building a Grading System with Python:

Bakare sukurat Aderonke — Sun, 22 Dec 2024 16:44:53 +0000

Hello Dev community!

I’m excited to share my Grading System Workbook, which is one of my first Python projects! As I’m diving deeper into Python, I wanted to create something practical that could be used to calculate grades efficiently based on various input criteria.

Project Overview

This project involves creating a grading system where grades are calculated automatically based on scores and other factors like weightage. The script takes inputs such as student scores for different assignments or exams and outputs the final grade, making it a time-saver for anyone managing multiple students.

Key Features:

Input Flexibility: Users can input multiple scores for different categories (assignments, exams, etc.).

Weighted Grading: The script calculates grades based on weighted criteria (e.g., exams = 60%, assignments = 40%).

Final Grade Calculation: The program outputs the final grade and gives feedback based on the score.

Learning Highlights:

How to manage user inputs and process them with Python.

Implementing a weighted grading system for accurate results.

Using functions to make the code modular and reusable.

I’m sharing the full code on my GitHub and I’d love to hear your thoughts, improvements, or any questions you have about the project. Feel free to explore and share your feedback!

Looking forward to engaging with the community and learning more!