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⏱ 2h 36m📚 26 lessons
Estimating Costs for Cloud Analytics Platforms
Learn how to forecast, model, and manage the total cost of ownership for cloud data and analytics workloads.
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About this course
Understanding the true cost of cloud analytics is essential for designing scalable, budget-conscious data platforms. This text-based course guides you through the foundational principles of calculating and forecasting cloud data expenses without unexpected billing surprises.
You will read through clear explanations and structured cost-modeling exercises that break down compute, storage, networking, and licensing variables. By exploring core FinOps principles, you will gain practical strategies to evaluate modern data stacks and make informed financial decisions for analytical architectures.
What you'll learn:
- Understand key pricing models across modern cloud data warehouses and lakehouses
- Calculate storage, compute, and data transfer costs accurately
- Apply FinOps frameworks to monitor, allocate, and forecast ongoing cloud spend
- Evaluate trade-offs between serverless architectures and provisioned instances
- Identify cost-optimization strategies such as resource scaling, data lifecycle policies, and caching
The course begins with foundational cloud billing terminology and core architectural components before moving into step-by-step cost calculation models and financial management practices.
This course is designed for data analysts, project managers, and aspiring cloud engineers looking to master analytics cost estimation. No advanced math or prior cloud architecture experience is required.
Start reading today to build predictable and cost-effective cloud analytics platforms.
Course contents
What you'll get
📜Certificate of completion Add it to your LinkedIn profile
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⚡Short & focused 2h 36m of practical content
Certificate of completion
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