📘 Welcome to CDI – Database Management

Why Database Management in CDI?

Every advanced data science or bioinformatics project relies on structured data. Before you can run machine learning models, sequence analyses, or large-scale dashboards, you need to know where your data lives and how to manage it.

This guide gives you that foundation. You’ll learn to set up, query, and integrate databases in a way that supports everything else you’ll encounter in CDI’s ecosystem.

🎯 Who this guide is for

  • Students and researchers starting with structured data
  • Analysts who want to move beyond Excel into SQL + Python
  • Developers building pipelines or applications powered by databases

🛠 What you’ll learn

A progressive path from setup to automation:

  1. Install and configure XAMPP with MySQL locally
  2. Write and run SQL queries (SELECT, WHERE, ORDER BY)
  3. Perform CRUD operations (INSERT, UPDATE, DELETE) safely
  4. Use JOINs to combine data across tables
  5. Connect SQL + Python (via mysql-connector-python and pandas)
  6. Export, import, and manage databases in real projects

🧭 How to use this guide

Each entry follows the CDI Q&A format:

How do you… → Explanation → SQL/MySQL Code → Python Code (if applicable) → Learning Outcome → Takeaway

📌 Note on order:

SQL creates the structure; Python builds on it.

  • Run SQL first when creating new databases/tables or seeding data.
  • Python can run directly when querying, updating, or automating existing structures.

🧠 Key takeaway: Database Management is not an isolated skill. It’s the backbone of every other CDI domain — from Bioinformatics to Cloud, from Machine Learning to Visualization. Once you understand databases, you unlock the ability to manage all kinds of complex data.

Are you ready to master databases from query to code? Let’s begin with Q1.