1.10 Self-test

Define "data-intensive" and contrast it with "compute-intensive."

Name the five standard building blocks and the job each does.

Give four differences between OLTP and OLAP access patterns. Which one drives the storage layout in Ch 4?

Why can't analysts just query the OLTP databases? Give all four reasons, and say which one is organizational rather than technical.

What is the difference between ETL and ELT, and why did ELT become more common?

Why doesn't HTAP eliminate the need for a data warehouse? Give the structural reason, not the performance one.

What is a data lake, and what specific data-science needs motivated it? What is the sushi principle?

Define system of record and derived data. Why is the distinction "not a property of the tool"?

Give three concrete downsides of a cloud service that all reduce to "you have no control."

What does "separation of storage and compute" actually mean, and why do cloud-native systems avoid virtual disks?

Why are local instance disks treated as an ephemeral cache?

In the cloud era, what does capacity planning become, and what does performance optimization become?

List five of the nine legitimate reasons to build a distributed system. Which two cannot be satisfied by a single machine at any price?

Why is "the request timed out" fundamentally different from "the request failed"?

Give three reasons a single machine may beat a cluster.

What problem are microservices actually solving? When are they unnecessary overhead?

Give four ways HPC differs from cloud computing in its assumptions about failure and trust.

Why does GDPR's right to erasure conflict with append-only log designs? Name two places a deletion must also reach.

State the data minimization principle and the philosophy it opposes.