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Flashcards in Chapter 7: Processing Data Deck (38)
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1

desktop software

applications that assist one user in performing certain tasks

2

enterprise software

contains applications that assist multiple users within an organisation

3

embedded software

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

4

firmware

software that is stored on non-volatile memory cards

5

transaction processing system (TPS)

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

6

batch processing

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)

7

online transaction processing (OLTP)

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

8

enterprise systems

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

9

enterprise resource planning

integrates the core functions of an organisation into a homogeneous system

10

customer relationship management

integrates data from customers that can be used by different departments

11

Database management systems (DBMS)

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

12

data warehouse

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

13

e-discovery

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

14

data mart

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

15

data aggregators

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

16

business intelligence tools

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

17

ad hoc reporting tools

enable users to create their own report and easily modify them

18

online analytical processing (OLAP)

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

19

data cubes

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

20

legacy systems

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

21

data mining

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

22

over-engineering

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

23

association rule mining

tries to identify the most common affinities between items

24

market basket analysis

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

25

support s(X)

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

26

confidence c(X-->Y)

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

27

pruning

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

28

clustering

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

29

K-means clustering

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

30

Characteristics of big data

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