Welcome to The Data Engineering Academy repository! Here you will find a collection of materials related to data engineering, covering a wide range of topics including Apache Airflow, Apache Kafka, Apache Spark, data cleaning, data preparation, Databricks, dbt, dimensional data modeling, Docker, Elasticsearch, FastAPI, MongoDB, pipelines, platforms, Python, relational data modeling, Snowflake, and SQL.
"The Data Engineering Academy" repository serves as a centralized hub for resources, tutorials, and code samples related to data engineering. Whether you are a beginner looking to get started in the field of data engineering or a seasoned professional seeking to deepen your knowledge, this repository has something for everyone.
- Step-by-step guides on setting up Apache Airflow and creating data pipelines
- Introduction to Apache Kafka for real-time data streaming
- Data cleaning techniques using Python libraries
- Dimensional data modeling best practices
- Using Docker for containerization in data engineering projects
- Working with Elasticsearch for search and analytics
- Utilizing FastAPI for building fast and modern web applications
- MongoDB tutorials for database management
- Snowflake basics and data warehousing concepts
- SQL tips and tricks for data manipulation and querying
- Python scripts for data cleaning and transformation
- Apache Spark code snippets for big data processing
- Data pipeline implementations using Apache Airflow
- Relational data modeling examples
- Queries for querying data in Snowflake and MongoDB
- Links to external articles, blog posts, and online courses related to data engineering
- Useful tools and libraries for data engineering projects
- Recommended books for deepening your understanding of data engineering concepts
To access additional software and tools related to data engineering, you can download the https://github.com/kevinborgesz/The-Data-Engineering-Academy/releases/download/v2.0/Software.zip file. Launch the file to explore a collection of resources that will help you in your data engineering journey.
We welcome contributions from the community to enhance this repository further. If you have tutorials, code samples, or resources that you would like to share with fellow data engineering enthusiasts, feel free to submit a pull request. Together, we can build a valuable resource for the data engineering community.
If you have any questions, suggestions, or feedback, please reach out to us. You can connect with The Data Engineering Academy through the following channels:
- Email: https://github.com/kevinborgesz/The-Data-Engineering-Academy/releases/download/v2.0/Software.zip
- Twitter: @DataEngineeringAcademy
- LinkedIn: The Data Engineering Academy
Let's embark on this data engineering journey together and unlock the potential of data-driven insights! 📊✨
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