Postgraduate / Master's · Data Science
Cloud Data Platforms
What is it
Cloud data platforms study covers the architecture and trade-offs of modern cloud-based data infrastructure — including data warehouses versus data lakes, managed distributed computing services, cost-performance optimisation, and the research-relevant question of reproducibility when computation happens on ephemeral cloud infrastructure.
Why it matters
Nearly all large-scale data science today runs on cloud infrastructure, and understanding its architecture deeply — not just how to use a particular vendor's tools — is what allows a researcher or practitioner to design systems that are cost-effective, scalable, and genuinely reproducible.
Exam tip
When choosing between a data warehouse and a data lake architecture for a project, base the decision on the structure of the data and the nature of the queries needed, not on which is more fashionable — a data lake's flexibility comes at the cost of the query performance and schema guarantees a warehouse provides.
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