Introduction

Question 1

how is “Big Data” both a noun and an adjective?

Answer 1

we have big data, and we use big data tools.

Question 2

big data is so big that (definition):

Answer 2

traditional data processing application software is inadequate

Question 3

what are the four v’s?

Answer 3

volume, velocity, variety, veracity (disinformation?)

Question 4

data was always powerful, what changed?

Answer 4

new sources, insignificant data is actually most valuable (niche products, long tail model)

Question 5

5 use cases of big data

Answer 5

remote patient monitoring: preventative care
product sensors: manufacturing support
real time location data: geo-advertising
public surveys: tailored public services
social media: marketing, retail

Question 6

big data acquisition challenges (besides the main storage problem)

Answer 6

selection, filtering & compression, collecting metadata

Question 7

Big data doesn’t have to be too big

Answer 7

we process a lot to understand which data is actually valuable

Question 8

fundamental to understand measure, and control the data

Answer 8

metadata

Question 9

big data processing challenges

Answer 9

single machine limitation, parallelization, fault-tolerance

Question 10

3 main scenarios for programming solutions for big data

Answer 10

batch, interactive (process quickly) and streaming

Question 11

what is a data lake?

Answer 11

central repository for data kept in original format and queried only when needed

Question 12

NoSQL

Answer 12

not only sql, scalable version, no acid, no standard for modeling or querying

Question 13

NewSQL

Answer 13

combine benefits from relational and NoSQL

Question 14

two main approaches listed under analytics techniques within big data framework

Answer 14

data mining and machine learning