Data Engineering using Kafka and Spark Structured Streaming

Course Overview

Skills and Knowledge Acquisition:
Participants in the "Data Engineering using Kafka and Spark Structured Streaming" course will acquire the following skills and knowledge:

Environment Setup: Learn how to set up a self-supported lab environment with Hadoop, Hive, Spark, and Kafka on a single-node Linux-based system, providing the foundation for data engineering tasks.

Kafka Fundamentals: Gain a deep understanding of Kafka, including creating Kafka topics, producing and consuming messages, and using Kafka Connect for data ingestion from web server logs into Kafka topics.

Data Ingestion: Explore data ingestion processes, including ingesting data from web server logs into Kafka topics and ingesting data from Kafka topics into HDFS as a sink.

Spark Structured Streaming: Understand the key concepts of Spark Structured Streaming, a powerful framework for real-time data processing.

Streaming Pipeline Development: Develop streaming pipelines that consume data from Kafka topics using Spark Structured Streaming, process the data, and write it to different target destinations.

Incremental Data Processing: Learn how to handle incremental data processing efficiently using Spark Structured Streaming.

Course Contribution to Professional Growth:
This course offers significant contributions to professional growth:

Data Engineering Proficiency: Participants will become proficient data engineers capable of building streaming data pipelines, a skill in high demand across industries.

Hands-on Experience: The course provides hands-on experience in setting up the environment and working with Kafka and Spark Structured Streaming, enhancing practical skills.

Real-world Application: Learning to build streaming pipelines prepares professionals for real-world data engineering tasks, making them valuable contributors to data-centric projects.

Problem-Solving Skills: Participants will develop problem-solving skills related to data engineering challenges and gain the ability to design and implement efficient data processing solutions.

Suitability for Preparing Further Education:
The "Data Engineering using Kafka and Spark Structured Streaming" course is suitable for individuals preparing for further education or seeking to deepen their knowledge in the field of data engineering:

Graduate Studies: Students pursuing advanced degrees in data engineering, computer science, or related fields can use this course as a foundation for deeper exploration of data engineering technologies.

Certification: Those planning to pursue certifications related to data engineering or real-time data processing can benefit from this course as a preparation resource.

Professional Development: IT professionals looking to expand their knowledge of data engineering, Kafka, and Spark Structured Streaming can use this course to enhance their expertise and prepare for further career advancement.