Big Data

Question 1

Big Data

Answer 1

An exponential growth in the amount of data between 2009-2020; the sheer growth is what makes big data big.

Question 2

Your data

Answer 2

Social medias will scrape everything you type or read to formulate ads. Anything you sign up or use for free will use or sell data

Question 3

What is big data?

Answer 3

All encompassing term including data, data frameworks and the tools and techniques used to process and analyse data

Question 4

5 ‘V’s of Big Data

Answer 4

Volume, Velocity, Variety, Veracity and Value

Question 5

Volume

Answer 5

Data at Rest: huge volumes of data generated from various sources such as social media, machines, networks and interactions

Question 6

Velocity

Answer 6

Data in Motion: refers to the speed at which data is being created in real time

Question 7

Variety

Answer 7

Data in Many Forms: data is gathered from multiple forms: pdfs, emails, video, social media posts, location etc.

Unstructured sources of data pose issues for data analysis and storage

Question 8

Veracity

Answer 8

Data in Doubt: uncertainty due to inconsistency and incompleteness, ambiguities, latency, deception and approximations

Question 9

Value

Answer 9

Data in Worth: value of the data to a business in terms of its ability to generate profit

Question 10

Structured Data

Answer 10

Guarantees that every entry of data has the same format e.g spreadsheet/csv columns

Question 11

Unstructured Data

Answer 11

Search results; website links, images, videos - all in different formats and structures

Question 12

Semi-structured data

Answer 12

XMR document: a combination of both structured and unstructured data. Structured in form, but with less constraints than structured data

Question 13

Data Ubiquity

Answer 13

Automatic data capture, opening up of existing data, simulations, approximations, synthetic data, exponential growth in storage, increase in bandwidth, faster algorithms

Reason exponential growth of data

Question 14

Examples of Big Data

Answer 14

NYSE generates one terabyte of new trade data per day
Facebook generates 4 petabytes of data per day
Single jet engine can generate 10 terabytes of data per flight
Walmart processes 40 petabytes of data per day

Question 15

Data-Information-Knowledge-Wisdom Model

Answer 15

1. Raw data (red)
2. Meaning of data (Traffic light has turned red)
3. Context of data (The traffic light I’m driving towards has turned red)
4. Data is then applied (Stop the car)

Question 16

Issues in Big Data

Answer 16

• Data is not knowledge - it is an upstream of information

- Possible to be data rich but information poor (DRIP)

Question 17

Data Science

Answer 17

Data science is concerned with analysing primary or experimental data

Question 18

Descriptive analytics

Answer 18

Transactional and interactional data used to identify trends

Question 19

Diagnostic analysis

Answer 19

Historical data can be measured against other data to find out why something happened

Question 20

Predictive analysis

Answer 20

Tells us what is most likely to happen via diagnostic and descriptive analytics

Question 21

Prescriptive analysis

Answer 21

Prescribe what action to take to eliminate a future problem or take advantage of a trend