Master Real-Time Data Engineering: Build a Smart City End to End Streaming Pipeline with Kafka, Spark, AWS & Docker
In this comprehensive Udemy course, you’ll be building a sophisticated Smart City End to End Realtime data streaming pipeline, covering every aspect from data ingestion to processing, and finally storage and visualization.
What you’ll learn
- Participants will gain a thorough understanding of data engineering concepts, including data ingestion, processing, storage, and visualization..
- Through practical demonstrations and coding exercises, participants will gain hands-on experience with a variety of industry-standard tools and technologies.
- By following along with the project setup, coding, and deployment process, participants will acquire the skills needed to build and deploy real-world solutions.
- Participants will encounter challenges and learn how to troubleshoot common issues that arise during the development and deployment of a data streaming pipeline.
- Participants will be well-equipped to pursue career opportunities in data engineering, IoT, cloud computing, and related fields..
Course Content
- Introduction –> 2 lectures • 3min.
- System Architecture –> 4 lectures • 24min.
- IOT Data Producer –> 8 lectures • 53min.
- Realtime Streaming Consumer –> 4 lectures • 41min.
- Data Transformation on AWS –> 4 lectures • 26min.
Requirements
In this comprehensive Udemy course, you’ll be building a sophisticated Smart City End to End Realtime data streaming pipeline, covering every aspect from data ingestion to processing, and finally storage and visualization.
Throughout this hands-on course, you’ll leverage an arsenal of industry-leading tools and technologies, including Apache Kafka for high-throughput, fault-tolerant messaging, Apache Spark for real-time data processing, Docker for containerization, and a suite of AWS services such as S3, Glue, Athena, IAM, and Redshift for cloud-based data storage, management, and analytics.
What’s in the course?
- Architect a Smart City End to End Realtime data streaming pipeline
- Set up and configure Docker containers for development and deployment
- Code IoT service producers for generating diverse data streams including vehicle information, GPS coordinates, traffic updates, weather conditions, and emergency incidents
- Stream data into Apache Kafka for real-time processing and distribution
- Utilize AWS services including S3, Glue, Athena, IAM, and Redshift for cloud-based data storage, management, and analytics
- Configure S3 buckets with policies and manage IAM roles and credentials for secure access
- Use AWS Glue for data cataloging and transformation, enabling seamless integration with downstream analytics tools
- Query data stored in AWS S3 with Athena, executing powerful SQL queries on your data lake
- Set up and manage a scalable data warehouse with AWS Redshift for advanced analytics and visualization
- Troubleshoot, debug, and optimize your streaming solution for maximum performance and reliability
- Build a portfolio project showcasing your proficiency in real-time data engineering and cloud-based analytics
But that’s just the beginning! You’ll delve into the intricacies of AWS setup, learning how to configure S3 buckets with policies, manage IAM roles and credentials, and leverage AWS Glue for data cataloging and transformation. With Athena, you’ll execute powerful queries on your data lake, while Redshift will serve as your data warehouse for scalable analytics.
By the end of this course, you’ll not only have built a fully functional Smart City data pipeline, but you’ll also have polished your skills in troubleshooting, debugging, and optimizing your streaming solution.
Enroll now and unlock the door to endless possibilities in the realm of data engineering!