Streaming data pipeline using Confluent Kafka & Google Cloud

Course Overview

In this hands-on course, participants will follow a step-by-step approach to build a real-time streaming analytics data pipeline that integrates Confluent Kafka with Google Cloud Platform services. Learners will design a pipeline that streams data from Kafka into Google Cloud Storage, processes it with Dataflow, stores it in BigQuery, and finally visualizes operational insights using Looker Studio. This practical journey ensures participants not only grasp the concepts but also apply them directly in a cloud-native environment.

Google Cloud Platform Experience

On the GCP side, participants will gain exposure to key services including Cloud Storage, Dataflow, BigQuery, and Looker Studio. They will also learn essential skills in logging, monitoring, troubleshooting, and configuration, which are critical for building secure, scalable, and reliable streaming applications in the cloud.

Confluent Kafka Experience

On the Kafka side, learners will set up a fully managed Kafka cluster, create topics for message streaming, configure a Datagen Source Connector to simulate real-world data ingestion, and integrate with GCP Storage Sink Connector. This provides valuable hands-on experience with enterprise-grade Kafka infrastructure—without the complexity of managing it manually.

Learning Outcomes

By the end of the course, participants will have:

• Built a working, scalable streaming analytics pipeline.

• Gained insights into cloud-native architectures and streaming design patterns.

• Acquired hands-on skills directly applicable to real-world projects and professional roles.

Who Should Attend

This course is ideal for Cloud Engineers, Data Engineers, Product Owners, Product Managers, Scrum Masters, and Technology Leaders seeking practical experience in building real-time streaming analytics pipelines with Confluent Kafka and Google Cloud.