Data Engineering with Google Dataflow and Apache Beam on GCP

Master Data Engineering with Google Dataflow and Apache Beam on GCP 🚀

Welcome to your journey into the world of high-performance data processing! This course, led by the experienced Cassio Alessandro de Bolbac, is your gateway to understanding and leveraging the power of Apache Beam and Google Dataflow within the Google Cloud Platform (GCP) ecosystem. 🧙‍♂️✨

Course Overview:

Dive into the essence of data engineering with a focus on Apache Beam – a unified model for defining both batch and streaming data-parallel processing pipelines. This course is designed to guide you through the core concepts and practical applications of Apache Beam, culminating in deploying your pipelines on Google Dataflow.

What You'll Learn:

🚀 Understand Your Inner Workings

• Gain insights into how data flows are constructed and managed.

💡 What Are Your Benefits

• Discover the advantages of using Apache Beam for your projects.

⚙️ Local Development with Google Colab

• Set up Apache Beam on your local machine without any complex installation processes.

🛠️ Main Functions of Apache Beam

• Learn about the key functionalities and how they can be applied to real-world scenarios.

💻 Configure Apache Beam Python SDK Locally

• Get hands-on experience with configuring the Apache Beam SDK for local development.

📦 Deploy on Google Dataflow

• Understand how to deploy your pipeline into a Batch pipeline on Google Dataflow.

Course Features:

• Dynamic Content: Receive updates to ensure you're learning the most current practices and techniques.
• Real-World Applications: Engage with use cases that demonstrate the practical power of Apache Beam and Google Dataflow.
• Python Knowledge Assumed: While this course does not teach Python from scratch, a good understanding of Python basics is necessary for full comprehension.
• Google Dataflow Deployment: If you plan to deploy pipelines on Google Dataflow, you'll need to set up a free account in GCP (which requires a credit card).

Course Requirements:

✅ Python Basics

• You should have a grasp of Python fundamentals, including functions, objects, and data types.

✅ Python Environment Setup

• Ensure Python 3.7 or newer is installed on your local machine before starting section 4.

✅ Google Cloud Platform Account

• Create a free account on GCP to follow along with the Google Dataflow deployment sections.

Course Schedule:

📅 Section 2 – Concepts

• We'll explore the foundational concepts of data engineering and Apache Beam.

🛠️ Section 3 – Main Functions

• Delve into the core functionalities of Apache Beam that make it a robust choice for data processing.

🚀 Section 4 – Apache Beam on Google Dataflow

• The crown jewel: learn to deploy your Apache Beam pipelines onto Google Dataflow and scale your data processing needs.

Join Us on This Data Engineering Adventure! 🌟

As you embark on this course, remember that each piece of knowledge you gain is a step towards becoming a proficient data engineer. The journey may seem simple, but the intentions behind this course are grand—to share valuable insights at an affordable price.

Your support through a kind rating at the end of the course helps keep this and future courses accessible to all who seek to learn and grow in the field of data engineering. Thank you for your investment in knowledge and your contribution to our community. Let's unlock the potential of data together! 🤝💫

Enroll Now and Transform Your Data Handling Skills with Apache Beam and Google Dataflow! 📈👨‍💻💼