Using Kafka on Confluent

External: Coursera Courses ↗ · Coursera

Open Course on External: Coursera

Free to audit · Opens on External: Coursera

Using Kafka on Confluent

Coursera · Intermediate ·🔄 Data Engineering ·3mo ago

Key Takeaways

Deploys Kafka on Confluent for real-time data handling and event streaming

Original Description

Enhance your data engineering expertise with practical skills in real-time data handling and event streaming using Confluent Kafka. This course offers direct, hands-on experience in setting up and managing Kafka clusters, connecting to diverse data sources, and building robust data pipelines for modern applications. Throughout this course, you'll explore the industry-specific applications of and delve into various features and functionalities. By the end of this course, you will be able to: - Know the architecture of Kafka and Confluent. - Explain the importance of Kafka Connect used to connect to other data sources. - Assess the capabilities of producers for publishing data records and consumers for retrieving data. - Applying concepts of Kafka to manage data. - Interpret replication and Kafka streams on Confluent. - Explore Kafka's full data handling capabilities on Confluent. This course is suited for freshers, IT professionals, data architects, and project managers looking to advance in streaming data and event-driven architecture. Basic understanding of RDBMS and data management will be useful but is not mandatory. Gain the confidence and technical skillset to architect, manage, and scale real-time data solutions with Confluent Kafka.
Watch on External: Coursera ↗ (saves to browser)
Sign in to unlock AI tutor explanation · ⚡30

Related Reads

📰
What Can We Do When Memory Becomes the New Bottleneck in Data Engineering?
Learn how to overcome memory bottlenecks in data engineering using Pandas chunking, Dask, and Polars, and why it matters for processing large datasets
Towards Data Science
📰
Migrate from Ponder to Envio HyperIndex
Learn to migrate your indexer from Ponder to Envio HyperIndex to scale your data management
Dev.to · Envio
📰
Data Backfilling with Apache Airflow: Architectures and Implementations for Historical Data Processing
Learn how to implement data backfilling with Apache Airflow for historical data processing and improve your data pipeline's accuracy and reliability
Dev.to · Wangila russell
📰
Building a Production-Style Weather Analytics Pipeline from Scratch: ETL, ELT, Star Schema, and…
Learn to build a production-ready weather analytics pipeline from scratch using Python, DuckDB, and Apache tools, and understand the importance of ETL, ELT, and Star Schema in data engineering
Medium · Python
Up next
A Moment Frozen in Time | Arnav Iyengar | TEDxJenks Youth
TEDx Talks
Watch →