Introduction to Modelling

Question 1

what is metadata

Answer 1

data about data

Question 2

what is data

Answer 2

unprocessed information

Question 3

what is information

Answer 3

data associated together

Question 4

what is knowledge

Answer 4

understanding information

Question 5

what sort of software manages data

Answer 5

file formats for particular applications .xls .doc .mp4 .jpg

specialist data management applications eg covid tracker

group project last year

Question 6

4 ways of adding structure to data files

Answer 6

delimited text field
fixed length field
length-based field
identified field

Question 7

what is a delimeter text field

Answer 7

choosing a special character eg comma or question mark that will not appear as a legitimate character within the info field and this will separate the individual data entries eg. comma separated file csv

Question 8

What is a fixed length field

Answer 8

use a fixed length for each information field eg 20 characters, padding out when length is less than fixed lenght

Question 9

what is the disadvantage of delimeter text

Answer 9

the character cannot be used legitimately in the information

Question 10

what is length based field

Answer 10

writing the length of the information field before the information so we know exactly how much space it takes up

Question 11

what is identified field

Answer 11

write the name of the information field and then value both represented as delimited text fields

Question 12

what are the two types of approaches of turning data into information

Answer 12

structured and unstructured

Question 13

what is a structured way of turning data into information

Answer 13

deliberately associate data together into information eg excel, data bases, datawarehouses

Question 14

examples of structured approaches of turning data into information

Answer 14

excel
databases
datawarehouses

Question 15

what is an unstructured way of turning data into information

Answer 15

loosely managed data together to serve a specific information need eg search engine

Question 16

example of an unstructured approach of turning data into information

Answer 16

search engines

Question 17

example of structured querying

Answer 17

SQL eg select exact criteria about data types

Question 18

What does SQL stand for

Answer 18

structured query language

Question 19

example of unstructured querying

Answer 19

keyword based, phrase based, search engine

Question 20

examples of structured results

Answer 20

exact, do need to estimate relevance, returns complete set of data that matches query criteria

Question 21

example of unstructured results

Answer 21

unsure of relevance, we must estimate relevance ourselves egGoogle page

Question 22

DBs stands for

Answer 22

databases

Question 23

ACID stands for

Answer 23

atomic
consistent
isolated
durable

Question 24

different type of data base models

Answer 24

relational
networked
hierarchal
onject-orientated

Question 25

most popular type of data base model

Answer 25

relational

Question 26

why didn't the other types of data base models take off

Answer 26

most investments made in relational

Question 27

DWs stands for

Answer 27

datawarehouses

Question 28

what is a datawarehouse

Answer 28

a subject orientated, nonvolatile, time-varients collection of data in support of management decisions

Question 29

uses of datawarehouses

Answer 29

data mining decision support OLAP (online analytical processing)

Question 30

what do data warehouses allow

Answer 30

trend view of data as timestamped

Question 31

information retrieval cycle in unstructured approach

Answer 31

``` information needed >>> query >>> query indexing >>> refined query >>> matching/retrieval >>> recommended objects >>> user review >>> ```

Question 32

what are four common challenges in managing data for enterprises and individuals

Answer 32

volume validity variety velocity

Question 33

how is volume a challenge in managing data

Answer 33

getting bigger ad bigger

Question 34

what are legacy sytstems

Answer 34

old information systems, as technology changes, information about enterprises or customers etc stays constant so this information is stored in a legacy system

Question 35

how is velocity a challenge in managing data

Answer 35

often data is time sensitive so much be processed in real time as it is streaming in order to maximize its value

Question 36

how is variety a challenge in managing data

Answer 36

variety in data eg text, audio, video, click streams, log files and more, difficult to label it all and agree

Question 37

how is validity a challenge in managing data

Answer 37

trade offs between data privacy and protection

Question 38

solution for coping with variety challenges

Answer 38

natural language processing semantic web technologies

Question 39

what is the difference between natural language processing and semantic web technologies

Answer 39

NLP is about understanding the context and matching based on that semantics is more about labelling things right anf agreeing on the labels

Question 40

solution for coping with volume challenge

Answer 40

outsource information management and technologies eg cloud

Question 41

solution for coping with validity challenges

Answer 41

GDPR lots of work going on about this at EU level data ethics data privacy

Question 42

what does GDPR stand for

Answer 42

general data protection regulations