LookerStudio101
LookerStudio101: Interactive Dashboards & Data Visualization 🔍
Install / Use
/learn @kaopanboonyuen/LookerStudio101README
README.md
LookerStudio101: Interactive Dashboards & Data Visualization
Welcome to LookerStudio101, where you’ll learn to harness the power of Looker Studio (formerly Google Data Studio) to build stunning, interactive dashboards. Dive into two real-world labs—disaster analysis and healthcare data visualization—designed to sharpen your dashboard-building skills and transform data into insightful reports.
📚 Lecture Slides
Explore the Looker Studio lecture slides for each lab:
-
🌟 Basic LookerStudio101 View Slide: Basic_LookerStudio101.pdf
-
🚀 Advanced LookerStudio101 N/A
👨🏫 Instructor
Teerapong Panboonyuen (P'Kao), Ph.D.
- Email: teerapong.pa@chula.ac.th
- Email: panboonyuen.kao@gmail.com
Lab Overview
🌀 Lab 1: Disaster Analysis Dashboard
In this lab, you’ll create a global disaster dashboard, exploring data on tsunamis, floods, and earthquakes. Your goal is to visually represent disaster occurrences around the world—map the locations, analyze the severity, and gain actionable insights to help address global challenges.
Dataset:
You can download the dataset for global disaster data here: Download Disaster Dataset (CSV)
🏥 Lab 2: Thailand Clinical Resource Dashboard
In this lab, you’ll create a dashboard to visualize Thailand’s clinical resources. The focus is on mapping and analyzing healthcare facilities, resources, and their distribution across Thailand, helping users make informed decisions regarding the healthcare landscape.
Dataset:
You can download the dataset for clinical resources here: Download Thailand Clinical Resources Dataset (CSV)
📊 Assignment 1: Data Exploration & Visualization 🚀
What’s the Deal?
For Assignment 1, you're free to choose any public dataset (or your own, like YouTube analytics, Shopee/Lazada sales, etc.). The task is simple: ask 5 meaningful questions about your data and use Looker Studio to create a dashboard that visually answers them.
What You Need to Do:
- Pick your dataset — Choose something that excites you.
- Ask 5 insightful questions — Dive into trends, patterns, or new insights.
- Visualize the answers — Use Looker Studio to create your dashboard.
🔗 Resources:
How to Get Started
Step 1: Clone the Repository
git clone https://github.com/kaopanboonyuen/LookerStudio101.git
cd LookerStudio101
Step 2: Download the Datasets
Make sure to download the CSV files for the labs:
- Disaster Analysis Dataset
- Thailand Clinical Resources Dataset
Step 3: Start Exploring Looker Studio
Sign in to Looker Studio and begin building your interactive dashboards. If you need assistance, consult the Lecture Slides.
Step 4: Build Your Dashboard
For each lab, you will:
- Connect the CSV files to Looker Studio.
- Apply filters, create calculated fields, and blend datasets.
- Design an intuitive, visually stunning dashboard to convey insights.
References & Resources
To further enhance your skills, refer to these resources:
- Kaggle Code Notebooks
- Stanford CS230 - Deep Learning
- Stanford Python Courses
- MIT OpenCourseWare: Introduction to Python
- Stanford CME193
- Python 101 by Chulalongkorn University
- Beautiful.ai - Presentation Tools
- Knowi vs Looker Comparison
License
This project is licensed under the MIT License - see the LICENSE file for details.
Disclaimer
The datasets and lecture materials provided in this repository are for academic use only, intended solely for classroom instruction. Some datasets may contain personal or sensitive information, and users must comply with all applicable data protection regulations, including the Personal Data Protection Act (PDPA). Any data scraped from platforms such as Twitter is for educational purposes only and must not be used for commercial or unauthorized activities.
Redistribution, modification, or public sharing of these materials without explicit permission is prohibited. By using these resources, you agree to follow these guidelines and understand that any misuse may result in academic or legal consequences.
Security Score
Audited on Jan 4, 2026
