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Stream & Optimize Real-Time Data Flows

By Coursera on Coursera · Data Science
Price
$49

About This Course

Master the design, implementation, and optimization of production-ready streaming data pipelines using Apache Kafka and Flink. This intermediate-level course teaches you to evaluate log configurations against governance requirements (PCI-DSS, GDPR, SOC2) and cost constraints, design stream processing topologies that join and aggregate data in real time with exactly-once semantics, and optimize pipelines through partition tuning, compression, and cost modeling. You'll work through hands-on labs that mirror real-world scenarios at DoorDash, Netflix, and Robinhood: comparing retention policies against compliance rules, building a Kafka Streams application that joins orders and payments to calculate 5-minute revenue totals, and diagnosing performance bottlenecks to meet SLAs within budget. Intermediate data engineers and platform engineers who build or operate real-time streaming systems and want to master Kafka/Flink governance, joins, windowing, and cost-optimized scaling. Understanding of distributed systems, basic Apache Kafka knowledge, familiarity with SQL and streaming concepts, Python or Java programming experience. By the end, you'll design and optimize a multi-tenant streaming platform with governance controls—skills directly applicable to streaming data engineer, real-time platform engineer, and data infrastructure roles.

Instructor

Coursera

Frequently Asked Questions

How much does Stream & Optimize Real-Time Data Flows cost?
Stream & Optimize Real-Time Data Flows costs $49. Check the course page for current pricing and available discounts.
Who teaches Stream & Optimize Real-Time Data Flows?
Stream & Optimize Real-Time Data Flows is taught by Coursera, Coursera.
What skill level is Stream & Optimize Real-Time Data Flows for?
This course is designed for intermediate learners.