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
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Gain insight into a topic and learn the fundamentals.
Advanced level
Recommended experience
2 hours to complete
Flexible schedule
Learn at your own pace
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.
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Recently updated!
February 2026
Taught in English
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This course is part of the DataOps: Automation & Reliability Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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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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