1. Introduction

This section covers the fundamental motivations and high-level concepts behind Big Data.

• (HS18) Why did batch processing become necessary? (e.g., latency improved at a lower rate than throughput).
• (HS18) Name the three Vs of Big Data.
• (HS19) What are the typical current values and units for HDD capacity, bandwidth, and latency?
• (HS18) Map the prefixes of the international system of units (Peta, Exa, Zetta, etc.) to the number of zeros.
• (HS18, HS19) True/False questions about scaling up vs. scaling out.
• (HS19) Which four database technologies are commonly referred to as NoSQL?
• (HS20, HS21) True/False questions about capacity, latency, and throughput over time.

2. Lessons learned from the past

This section focuses on the foundational principles derived from traditional relational database systems.

Theory: Data independence means that the logical view on the data is cleanly separated, decoupled, from its physical storage. A RDBMS exposes a table as logical model, together with logical building block for manipulating it.

• (HS18, FS21) Codd's 1970 paper introduced which concepts? (relational algebra, data independence).
• (HS17, HS18) Questions on Relational Algebra equations and their validity under set and bag semantics.
• (HS17, HS18) Questions about normal forms and their properties.
• (HS20) What does each letter in ACID stand for?
• (FS21) In "ACID database" terminology, what does the A stand for? (Atomicity).
• (HS20, HS21) Is the SQL language declarative, procedural, or functional?