5 FREE End-To-End Data Engineering Projects
You will learn AWS, GCP, and Azure just by doing these 5 projects
These projects have combined 2 Million+ views, there’s a reason behind it.
Data engineering might sound like a complex field, and honestly, it can be. But, like learning to ride a bike, it becomes easier and more intuitive with practice.
To help you get started or to give your skills a boost, I’ve picked out five awesome projects you can work on for free. They’re not just any projects; they’re fun, they’re engaging, and they cover a range of topics and tools. Let’s dive in!
1. YouTube Data Analysis
Ever wondered what makes a YouTube video popular? In this project, you’ll get to play with real YouTube data to find out. You don’t need to be a data wizard to begin. You’ll learn to use Python, a programming language loved for its ease of learning, along with PySpark for handling big data. Plus, you’ll get a taste of SQL (a language for managing data) and various AWS (Amazon Web Services) tools like Athena, Glue, Redshift, and S3. These tools are big names in the data world, and you’ll learn how they work together to solve problems.
Skills you’ll develop:
- Coding with Python and PySpark
- Basic SQL for data management
- Understanding and solving real-world problems
- Using AWS tools for data projects
2. Twitter Data Pipeline with Airflow
Twitter is a goldmine of data. In this project, you’ll learn how to automate the process of collecting, processing, and storing Twitter data. Airflow helps you schedule and organize these tasks, and you’ll see how it works first-hand. The project also introduces you to Tweepy (a tool for accessing Twitter data) and Pandas (a Python library for data analysis). It’s a great way to get comfortable with writing ETL (Extract, Transform, Load) jobs, a common task for data engineers.
Skills you’ll develop:
- Python Programming
- Automating tasks with Airflow
- Data collection and analysis
- Working with APIs and cloud storage
3. Real-Time Stock Market Analysis
Imagine being able to predict stock market trends as they happen. This project brings you closer to that reality. You’ll build an application that uses Python and Kafka (a platform for handling real-time data streams) to analyze stock market data in real time. Setting up Kafka on an EC2 instance (a type of server) and creating a data pipeline is part of the fun. It’s a project that feels like magic but is grounded in practical skills.
Skills you’ll develop:
- Building real-time applications
- Understanding Kafka for Data Streams
- Setting up cloud servers
- Real-time data analysis
4. Uber Data Analytics on GCP
Uber’s data is vast and varied, making it perfect for an analytics project. You’ll learn how to make sense of raw data, build a data model, and write scripts for ETL tasks. This project also introduces you to mage, a modern tool for building data pipelines, and SQL for data analysis. Plus, you’ll be working on Google Cloud Platform (GCP), one of the leading cloud services, giving you hands-on experience with a top-notch technology stack.
Skills you’ll develop:
- Data modeling and analysis
- Writing and automating ETL scripts
- SQL querying
- Working with cloud-based data tools
5. Olympic Data Analytics on Azure
The Olympics generate a ton of data. In this project, you’ll learn how to extract this data from APIs and analyze it using Azure, Microsoft’s cloud platform. You’ll get to use services like DataBricks for big data, DataFactory for data integration, and Synapse Analytics for large-scale data analysis. It’s a project that will teach you how to handle data at scale and provide insights that could influence future Olympic strategies.
Skills you’ll develop:
- Extracting data from APIs
- Using Azure services for data engineering
- Writing Spark code for data processing
- Advanced data analysis with SQL
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