Set Up a Professional Analytics Workspace (SQL, Python & Power BI)
🚀 This setup is the foundation for all PortfolioStack projects. If you want guided, job-ready projects you can showcase professionally then have a look at 👉 https://www.portfoliostack.io/?utm_so...
A clean, reliable analytics environment is a big advantages you can give yourself whether you’re learning data on your own or following PortfolioStack projects.
In this video, I’ll walk you through the exact setup I use for all PortfolioStack projects, which also works perfectly as a standalone analytics workspace for anyone who wants a fast, lightweight, professional environment for SQL, Python and data modeling.
By the end you’ll have a fully working setup that lets you focus on learning and building projects.
⏱️ Video Overview:
00:00 Welcome & Overview
00:31 Install Your Core Tools
01:06 Create Your Workspace Folder
02:09 Install Python Packages
02:51 Test Environment in VS Code
03:22 Test Environment in DBeaver
03:55 Continue Learning
👤 Who is this environment for?
✔ Anyone learning data analytics or data engineering
✔ Anyone wanting a clean environment for SQL + Python
✔ PortfolioStack students preparing for hands-on project modules
🛠️ What We’ll Do in This Setup (4-Step Summary):
✔ Install the core tools — VS Code, Python, DuckDB, and DBeaver.
✔ Create a clean PortfolioStack workspace with a reusable project structure and example DuckDB database.
✔ Install and verify Python + DuckDB using the required packages and a test script to confirm everything works.
✔ Connect your database to VS Code and DBeaver so you can run SQL queries and preview your tables instantly.
📦 Get all necessary script and files here on GitHub plus download from below links:
Scripts + Project Folder: https://github.com/aliahmadportfolios...
DBeaver: https://dbeaver.io/
Python: https://www.python.org/
VSCode: https://code.visualstudio.com/
Happy learning!
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