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 IT Education Association
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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There are 2 modules in this course
Learners will master evidence-based pipeline performance evaluation by systematically measuring execution metrics, analyzing runtime statistics, and making data-driven optimization decisions.
What's included
4 videos1 reading2 assignments
Learners will develop automation skills to create scripts that read configuration specifications and generate complete data transformation models, enabling scalable and consistent pipeline development.
What's included
3 videos2 readings2 assignments1 ungraded lab
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