Building a Realtime Streaming System for a Smart City

Master Real-Time Data Engineering: Build a Smart City End to End Streaming Pipeline with Kafka, Spark, AWS & Docker


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.

Requirements
Basic Python programming experience

Description
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!
Who this course is for:
Everybody interested in building scalable and efficient systems

More Info