Section 12 Chapter 72 - Big Data

Question 1

Big Data

Answer 1

Data that won’t fit into the usual containers due to its volume, velocity or variety

Question 2

Volume of Big Data

Answer 2

Too big to fit in a single server

Question 3

Velocity of Big Data

Answer 3

Very short amount of time to respond

Question 4

Variety of Big Data

Answer 4

Can be structured/unstructured

Question 5

Why the lack of structure common in Big Data is a problem (2)

Answer 5

• Analysing it is difficult

- Relational databases cannot be used as they require the data to be in a row-column format

Question 6

How Big Data can be analysed

Answer 6

machine learning

Question 7

Why the volume of Big Data is important

Answer 7

Relational databases don’t scale well across multiple machines

Question 8

What programming paradigm is most suited to Big Data

Answer 8

Functional

Question 9

How Big Data can be processed (with regards to volume)

Answer 9

Processing is distributed across multiple machines

Question 10

Why functional programming is suited to Big Data (2)

Answer 10

• No side effects (Statelessness)
• Higher order functions
• Assignment is forbidden, which makes parallel programming much easier

Question 11

Fact based model

Answer 11

An alternative to the relational data model. Immutable facts are recorded with timestamps rather than overwritten.

Question 12

Graph Schema

Answer 12

Data is stored as nodes, properties and edges

Question 13

Fact (In a fact based model)

Answer 13

A single piece of information