Welcome to CDI – Economics Data Analysis

Why Economics Data Analysis in CDI?

Modern economics is inseparable from data.
From GDP and trade balances to labor market surveys and household consumption, every economic insight comes from data collection, management, and analysis.

This guide provides the bridge between economic theory and data-driven practice.
You’ll learn not just what economic concepts mean, but also how to measure, query, and analyze them using real datasets and computational tools.

Who this guide is for

  • Students and researchers studying economics, econometrics, or development studies
  • Analysts working with economic indicators, survey data, or trade statistics
  • Policy professionals and business strategists who want evidence-based insights

What you’ll learn

A progressive path from fundamentals to applied analysis:

  1. Explore core economic indicators (GDP, inflation, unemployment, trade balances)
  2. Store and manage economic datasets in relational databases (SQL, MariaDB/MySQL)
  3. Perform descriptive and inferential analysis using SQL and Python (pandas, statsmodels)
  4. Apply econometrics: regression models, time-series, and forecasting
  5. Translate raw data into insights that support decision-making in policy and business

How to use this guide

  • Start with Q&A explanations of economic concepts
  • Practice with SQL and Python examples applied to real datasets (CSV, World Bank, IMF, UN data)
  • Use bookmarks to save important workflows and queries
  • Follow the workflow: concept → dataset → query → analysis → interpretation

Why it matters

Data transforms economics from theory into action.
By mastering both the concepts and the analytical tools, you’ll be able to work with complex, real-world datasets and provide insights that matter for economies, organizations, and communities.

Transition to Q&A

With this foundation, you’re ready to dive into the Q&A sections.
Each Q&A tackles a concrete economic problem—
whether it’s measuring GDP growth, modeling inflation, or forecasting unemployment—
and walks you through the process using step-by-step explanations, SQL queries, and Python code.

👉 The Q&A format is your companion for turning economic data into clear, actionable insights.