Chapter 7: Processing Data

Question 1

desktop software

Answer 1

applications that assist one user in performing certain tasks

Question 2

enterprise software

Answer 2

contains applications that assist multiple users within an organisation

Question 3

embedded software

Answer 3

designed for a specific purpose and that is often embedded in physical products

Question 4

firmware

Answer 4

software that is stored on non-volatile memory cards

Question 5

transaction processing system (TPS)

Answer 5

operational system that records data about fundamental activities within the organisation (can be to a specific department)

Question 6

batch processing

Answer 6

data is stored in a temporary storage and then processed as a single unit –> money transfers from banks (processing takes time and therefore delays occur)

Question 7

online transaction processing (OLTP)

Answer 7

data is immediately processed so that the current state of the system is always refelcted

Question 8

enterprise systems

Answer 8

made to combine collected and processed data from various departments of the company into a whole

Question 9

enterprise resource planning

Answer 9

integrates the core functions of an organisation into a homogeneous system

Question 10

customer relationship management

Answer 10

integrates data from customers that can be used by different departments

Question 11

Database management systems (DBMS)

Answer 11

collects and disseminates information that is created and used by multiple apps

Question 12

data warehouse

Answer 12

collect data and store it from various core transaction systems throughout the organisation and provide analyses and reporting tools

Question 13

e-discovery

Answer 13

information needs to be identified and recalled from archives for supporting lawsuits

Question 14

data mart

Answer 14

subset of data stored in a data warehouse –> contain a very concentrated part of the data of the organisation. Used to perform analyses on the processes to gain insight into a company

Question 15

data aggregators

Answer 15

companies that are purely focussed on collecting and selling data to other companies

Question 16

business intelligence tools

Answer 16

tools that help to merge, analyse and access data with the aim to support organisational decision making

Question 17

ad hoc reporting tools

Answer 17

enable users to create their own report and easily modify them

Question 18

online analytical processing (OLAP)

Answer 18

data is extracted from traditional databases, calculated, summarised and stored in data cubes

Question 19

data cubes

Answer 19

special databases that structure data across multiple dimensions, such as place, products and time

Question 20

legacy systems

Answer 20

obsolete information systems that are not designed to share data, are not compatible with new technologies and are not aligned with the current needs of an organisation

Question 21

data mining

Answer 21

using specific algorithms to detect hidden patterns and make models suitable for large data sets –> data must be consistent and clear and events in the data must reflect current and future trends

Question 22

over-engineering

Answer 22

when so many variables are included in a model that the solution found probably only works in the subset of data with which the solution was found

Question 23

association rule mining

Answer 23

tries to identify the most common affinities between items

Question 24

market basket analysis

Answer 24

looks at all individual transactions of a customer and then examines which products are bought together

Question 25

support s(X)

Answer 25

the fraction of transactions that contains a certain set of items X –> the number of times a certain combination occurs divided by the total transactions

Question 26

confidence c(X–>Y)

Answer 26

the fraction of transactions containing Y from the group of transactions containing X –> the number of times a combination occurs divided by the number of times that another product is purchased with this combination

Question 27

pruning

Answer 27

used to identify with high support. Within these bundles, looks for those with high confidence

Question 28

clustering

Answer 28

tries to minimise the sum of the distance between the core of the cluster and all observations belonging to this cluster

Question 29

K-means clustering

Answer 29

each data point is allocated to the nearest cluster centre and then the cluster centre is moved to minimise the total distance between the points

Question 30

Characteristics of big data

Answer 30

1. Velocity: speed in which data must be generated
2. Volume: size of the dataset that needs to be processed
3. Variety: different formats and characteristics of data
4. veracity: reliability of data

Question 31

analytics

Answer 31

combine classical statistics with artificial intelligence to derive achievable insights from big data

Question 32

machine learning

Answer 32

large amounts of data are used so that computers can improve the accuracy of actions and predictions without extra programming

Question 33

neural networks

Answer 33

are trained to use large historic data sets and to find patterns in them so that a model can be built that exploits the findings –> accuracy of the findings increases as the action is repeated

Question 34

expert systems

Answer 34

use rules or examples to finish tasks that imitate human expertise

Question 35

genetic algorithms

Answer 35

computers investigate possible solutions to a problem

Question 36

HADOOP

Answer 36

used for storage and analysis of large datasets

Question 37

4 advantages of HADOOP

Answer 37

1. scalability
2. flexibility
3. cost efficiency
4. fault tolerance

Question 38

blackbox method

Answer 38

hard to quantify the impact of a certain input variable on the outcome