Apache Spark Project World Development Indicators Analytics

World Development Indicators Analytics Project in Apache Spark for beginner using Databricks (Unofficial)

Description

Have you ever wondered how countries are compared in terms of GDP, literacy, life expectancy, trade, or poverty rates? Do you want to analyze and visualize global development data with Apache Spark and build powerful insights that tell the story of the world’s economic and social progress?

Welcome to “Apache Spark Project: World Development Indicators Analytics” — a hands-on, project-based course where you will learn to process, analyze, and visualize real-world datasets that capture the world’s development journey

This course focuses on using Apache Spark (with Databricks) to analyze the World Development Indicators dataset from the World Bank.  Through step-by-step guidance, you’ll not only learn Spark DataFrame operations and Spark SQL, but also apply them to real analytics use cases that explore critical development metrics

You’ll start from scratch — setting up your environment, understanding the dataset, and importing notebooks into Databricks   

Then, we’ll dive deep into hands-on analytics, answering meaningful questions such as:

• What is the GINI Index across countries, and what does it reveal about inequality?

• How do youth literacy rates compare worldwide?

• How do China and India perform in terms of trade as % of GDP?

• Which are the richest and poorest countries, and how have they changed between 1960 and 2014?

• How do life expectancy, infant mortality, and urban population growth vary across countries?

• How has GDP per capita evolved in rich vs poor countries over decades?

By the end of this project, you’ll be able to:

• Load and analyze large-scale structured datasets with Spark

• Apply Spark DataFrame APIs to generate development insights

• Perform country-level comparative analytics.

• Publish and share Databricks notebooks as reports.

• Build confidence in tackling real-world Spark projects.

This course is designed to give you practical, job-ready skills in Spark through a globally relevant project that connects data engineering, data analysis, and real-world development insights.

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