Chapter 9

Front 1

BI Analysis

Back 1

theprocess of creating business intelligence. *3 Fundamental categories: reporting, data mining,and knowledge management.

Front 2

BI Application

Back 2

The software component of BI Systems

Front 3

Business Intelligence (BI)

Back 3

the process of operational and other data tocreate information that exposes patterns, relationships and trends ofimportance to the organizations

Front 4

Business Intelligence Systems

Back 4

Informational systems that track BI

Front 5

BI Server

Back 5

a computer program that delivers application results in a variety of formats to various devices for consumption by BI users

Front 6

Cluster Analysis

Back 6

an unsuperviseddata mining technique whereby statistical techniques are used to identifygroups of entities that have similar characteristics *Can be used to find a certaindemographic/ geographic customer in a database

Front 7

Confidence

Back 7

In-marketbased terminology, the probability estimate that two items will be purchasedtogether

Front 8

Content Management Systems (CMS)

Back 8

Informationsystems that track organizational documents, web pages, graphics and relatedmaterials.

Front 9

Cookie

Back 9

a piece of data that is stored on the user’scomputer by a browser. Can be used to store shopping carts and also be used toimplement spyware.

Front 10

Cross-selling

Back 10

thesale of related products salespeople try to get consumers who buy product Xalso to buy product Y

Front 11

Data Aquisition (OCORC)

Back 11

in BI, the process of obtaining, cleaning,organizing, relating and cataloging data

Front 12

Data Mart

Back 12

datacollection that is smaller than the data warehouse, which addresses the needsof a particular department or functional area of the business

Front 13

Data Mining

Back 13

the applicationof statistical techniques to find patterns and relationships among data forclassification and predictions

Front 14

Data Triangulation (semantic security)

Back 14

concernsthe unintended release of protected data through the release of a combinationof reports or documents that are not protected

Front 15

Data Warehouse

Back 15

a facility for managing an organizations BI data

Front 16

Decision Support Systems

Back 16

another term used for BI systems

Front 17

Decision Tree

Back 17

a hierarchical arrangement of criteria for classifying customers, items, and other business objects

Front 18

Dimension

Back 18

a characteristic of OLAP

(purchase date, customer type, location)

Front 19

Drill down

Back 19

With an OLAP report, to further divide the data into more detail

Front 20

Dynamic Reports

Back 20

BI documents that are updated at the time they are requested

Front 21

Expert Systems

Back 21

knowledge-sharing systems that are created by interviewing experts in a given business domain and coding the rules used by those experts

Front 22

Expert Systems Shell

Back 22

Aprogram in an expert system that processes a set of rules, typically manytimes, until the values of the variables no longer change, at which point thesystem reports the results

Front 23

Granularity

Back 23

The level ofdetail in data

*Large granularity: customer name, balance *Small granularity: customer name, balance, orderdetails and payment history of every customer order

Front 24

Hadoop

Back 24

An open sourced program supported by Apache Foundation that manages thousands of computers

Front 25

Hyper-Social management knowledge

Back 25

The application of social media for the management delivery of organizational knowledge resoures

Front 26

If/ then ruls

Back 26

formal rules delivered from a decision tree (data mining) or by interviewing a human expert (expert systems)

Front 27

Knowledge Management (KM)

Back 27

The process of creating value from intellectual capital and sharing that knowledge with employees, managers, suppliers, customers and others

Front 28

Lift

Back 28

The ratio of confidence to the base probability of buying an item Lift shows how much the base probability changes when other products are purchased

Front 29

Map Reduce

Back 29

Two phase techniques for harnessing the power of thousands of computers working in parallel

1) Map phase: computers work i parallel

2) Reduce phase: separate computers are combined, eventually obtaining single results

Front 30

Market-Based Analysis

Back 30

A data mining technique for determining sales patterns. Shows the products that customers tend to buy together

Front 31

Measure

Back 31

data item of interest of an OLAP report. An item that is to be summed, averaged or processed in an OLAP cube

Front 32

Neutral Network

Back 32

a popular supervised data mining technique used to predict values and make classifications such as "good prospect" and "poor prospect"

Front 33

OLAP Cube

Back 33

a presentation of an OLAP measure with associated dimensions

Front 34

Online Analytical Processing (OLAP)

Back 34

A dynamic type of reporting system that provides the ability to sum count, average and perform other simple operations on groups of data. Uses can change the formal while viewing them

Front 35

Pig

Back 35

Query language used with Hadoop

Front 36

Publish Results

Back 36

the process of delivering business intelligence to the knowledge workers who need it

Front 37

Pull Publishing

Back 37

the mode where users must request BI results

Front 38

Push Publishing

Back 38

the mode where BI systems deliver business intelligence to users without a request from the user

Front 39

Regression analysis

Back 39

A type of supervised data mining that estimates the values of parameters in a linear equation. Used to determine the relative influence of variables on an outcome and also to predict future values of that outcome

Front 40

Reporting Application

Back 40

A business intelligence application that formats data by applying reporting tools to BI data