Did you know that two pipelines performing the same task can differ in run time by over 10x depending on design choices? Benchmarking and automation are essential for building fast, scalable, and cost-efficient data systems.

Automate, Optimize, and Benchmark Data Pipelines

Automate, Optimize, and Benchmark Data Pipelines
This course is part of DataOps: Automation & Reliability Specialization

Instructor: Hurix Digital
Access provided by Samsung Research, Bangalore
Recommended experience
What you'll learn
Performance measurement and evidence-based decisions rely on comparing execution metrics to improve data engineering efficiency.
Config-driven model generation cuts manual work, keeps projects consistent, and supports scalable data transformation.
Pipeline optimization uses repeated measurement and programmatic fixes to deliver lasting performance gains.
Modern data engineering succeeds by creating reusable, maintainable systems that adapt to changing needs while preserving performance.
Details to know

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February 2026
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