L 3.2 Information Systems Development + Big Data & Business Intelligence

Question 1

data drive organisations have

Answer 1

access to data
access to analytics
analytics and domain knowledge collaboration
data informed decision making

Question 2

Big data types

Answer 2

• structured data: transactions data
• semi-structured data: clickstreams or sensor data
• unstructured data: text, audio and video data, comments on socials

Question 3

bid data characteristics

Answer 3

• volume: amount of users
• velocity: how fast, posts per day
• variety: how many types of data, follows, comments, uploads

Question 4

data warehouse

Answer 4

stores data form different business processes, quick to access historical information for business intelligence

Question 4

databases

Answer 4

• places where things are stored like wikipedia, Spotify, amazon
• store data and make it accessible where and when needed
• can store organisational data ranging from inventory to demand forecasts

Question 5

relational databases (RDSMS)

Answer 5

• type of database
• most common, easy to implement and us
• relatively rigid, hard to scale
• attempts to balance efficiency of storage needs ease on retrieval and other factors by storing data in tablets linked via relationships

Question 6

NoSQL databse

Answer 6

-type of database
- flexible/scalable, often have ad-hoc depending on company needs
- easier than RDBMS therefore becoming more popular

Question 7

business intelligence and advanced analytics

Answer 7

• refers to tools and techniques for analysing and visualising past data
• improve business with data

Question 8

why do organisation need business intelligence and advanced analytics

Answer 8

• most businesses are data driven
• can better respond to ongoing threat and opportunities and plan for the future
• humans need to translate the output and turn it into action

Question 9

visual analytics

Answer 9

• combines data and human ability to spot patterns that are hard to express/questions systematically
• databases → BI software → visual analytics

Question 10

clustering

Answer 10

involves grouping similar data points together based on their features or attributes
goal is to discover hidden pattern or structures in the data

Question 10

spurious correlations

Answer 10

not a meaningful correlation

Question 11

advanced data analytics and AI

Answer 11

• through this we want to explain why things happen and predict what will happen in the future
• gain competitive advantage by innovation

Question 11

machine learning

Answer 11

using statistical tools to model relationships between variables

Question 12

text mining - NLP

Answer 12

• NLP: natural language processing
• a number of statistical methods to extract content from text data
• another way of reinforcement learning
• the more the internet is used the better is gets at understanding behaviours

Question 13

machine learning methods (4)

Answer 13

• regression
• classification
• clustering
• reinforcement learning

Question 14

regression

Answer 14

estimating the strength direction and significant of a correlation
(line regression, between -1 and 1)

Question 15

classification

Answer 15

AI learns classification from labelled examples and predict the classification of new images (ex. cat or dog)

Question 15

reinforcement learning

Answer 15

• the base of most learning AI
• learns by exploring a decisions space by trial and error
• very sophisticated by difficult to implement

Question 16

Natural language processing tasks

Answer 16

• sentiment analysis: positive or negative setence
• topic modelling: what is the text about
• net-word prediction: autocomplete