Using MIS Chapter 9

Question 1

BI Analysis

Answer 1

The process of creating business intelligence. The four fundamental categories of BI analysis are reporting, data mining, BigData, and knowledge management.

Question 2

BI Application

Answer 2

The software component of a BI system.

Question 3

BI Server

Answer 3

A Web server application that is purpose-built for the publishing of business intelligence.

Question 4

Business Intelligence (BI)

Answer 4

The processing of operational and other data to create information that exposes patterns, relationships, and trends of importance to the organization

Question 5

Business Intelligence Systems

Answer 5

Information systems that process operational and other source data to identify patterns, relationships, and trends and to make predictions.

Question 6

Cluster Analysis

Answer 6

An unsupervised data mining technique whereby statistical techniques are used to identify groups of entities that have similar characteristics. A common use for cluster analysis is to find groups of similar customers in data about customer orders and customer demographics.

Question 7

Confidence

Answer 7

In market-basket terminology, the probability estimate that two items will be purchased together.

Question 8

Content Management Systems (CMS)

Answer 8

Information systems that support the management and delivery of documentation including reports, Web pages, and other expressions of employee knowledge.

Question 9

Cookie

Answer 9

A small file that is stored on the user’s computer by a browser. Cookies can be used for authentication, for storing shopping cart contents and user preferences, and for other legitimate purposes. Cookies can also be used to implement spyware.

Question 10

Cross-Selling

Answer 10

The sale of related products to customers based on salesperson knowledge, market-basket analysis, or both.

Question 11

Data Acquisition

Answer 11

In business intelligence systems, the process of obtaining, cleaning, organizing, relating, and cataloging source data.

Question 12

Data Aggregator

Answer 12

See data broker 336???

Question 13

Data Broker

Answer 13

A company that acquires and purchases consumer and other data from public records, retailers, Internet cookie vendors, social media trackers, and other sources and uses it to create business intelligence that it sells to companies and the government. 336

Question 14

Data Mart

Answer 14

A data collection, smaller than a data warehouse, that addresses the needs of a particular department or functional area of a business.

Question 15

Data Mining

Answer 15

The application of statistical techniques to find patterns and relationships among data for classification and prediction.

Question 16

Data Triangulation

Answer 16

See semantic security. 362

Question 17

Data Warehouse

Answer 17

A facility for managing an organization’s BI data.

Question 18

Decision Support Systems

Answer 18

Some authors define business intelligence (BI) systems as supporting decision making only, in which case they use this older term as a synonym for decision-making BI systems.

Question 19

Decision Tree

Answer 19

A hierarchical arrangement of criteria that predict a classification or a value.

Question 20

Dimension

Answer 20

A characteristic of an OLAP measure. Purchase date, customer type, customer location, and sales region are examples of dimensions.

Question 21

Drill Down

Answer 21

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

Question 22

Dynamic Reports

Answer 22

Business intelligence documents that are updated at the time they are requested.

Question 23

Expert Systems

Answer 23

Rule-based systems that encode human knowledge in the form of if/then rules.

Question 24

Expert Systems Shells

Answer 24

A program in an expert system that processes a set of rules, typically many times, until the values of the variables no longer change, at which point the system reports the results.

Question 25

Granularity

Answer 25

The level of detail in data. Customer name and account balance is large granularity data. Customer name, balance, and the order details and payment history of every customer order is smaller granularity.

Question 26

Hadoop

Answer 26

An open-source program supported by the Apache Foundation that manages thousands of computers and which implements MapReduce.

Question 27

Hyper-social Knowledge Management

Answer 27

The application of social media and related applications for the management and delivery of organizational knowledge resources.

Question 28

If/Then Rules

Answer 28

Statements that specify that if a particular condition exists, then a particular action should be taken. Used for both expert systems and decision trees.

Question 29

Knowledge Management (KM)

Answer 29

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

Question 30

Lift

Answer 30

In market-basket terminology, 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. If the lift is greater than 1, the change is positive; if it is less than 1, the change is negative.

Question 31

MapReduce

Answer 31

A two-phase technique for harnessing the power of thousands of computers working in parallel. During the first phase, the Map phase, computers work on a task in parallel; during the second phase, the Reduce phase, the work of separate computers in combined, eventually obtaining a single result.

Question 32

Market-Basket Analysis

Answer 32

A data mining technique for determining sales patterns. A market-basket analysis shows the products that customers tend to buy together.

Question 33

Measure

Answer 33

The data item of interest on an OLAP report. It is the item that is to be summed, averaged, or otherwise processed in the OLAP cube. Total sales, average sales, and average cost are examples of measures.

Question 34

Neural Networks

Answer 34

A popular supervised data mining technique used to predict values and make classifications, such as “good prospect” or “poor prospect.”

Question 35

OLAP Cube

Answer 35

A presentation of an OLAP measure with associated dimensions. The reason for this term is that some products show these displays using three axes, like a cube in geometry. Same as OLAP report.

Question 36

Online Analytical Processing (OLAP)

Answer 36

A dynamic type of reporting system that provides the ability to sum, count, average, and perform other simple arithmetic operations on groups of data. Such reports are dynamic because users can change the format of the reports while viewing them.

Question 37

Pig

Answer 37

Query language used with Hadoop.

Question 38

Predictive Policing

Answer 38

Using data on past crimes to predict where future crimes are likely to occur.

Question 39

Publish Results

Answer 39

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

Question 40

Pull Publishing

Answer 40

In business intelligence (BI) systems, the mode whereby users must request BI results.

Question 41

Push Publishing

Answer 41

In business intelligence (BI) systems, the mode whereby the BI system delivers business intelligence to users without any request from the users, according to a schedule, or as a result of an event or particular data condition.

Question 42

Regression Analysis

Answer 42

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.

Question 43

Reporting Application

Answer 43

A business intelligence application that inputs data from one or more sources and applies reporting operations to that data to produce business intelligence.

Question 44

RFM Analysis

Answer 44

A technique readily implemented with basic reporting operations to analyze and rank customers according to their purchasing patterns.

Question 45

Rich Directory

Answer 45

An employee directory that includes not only the standard name, email, phone, and address, but also expertise, organizational relationships, and other employee data.

Question 46

Semantic Security

Answer 46

Concerns the unintended release of protected data through the release of a combination of reports or documents that are not protected independently.

Question 47

Static Reports

Answer 47

Business intelligence documents that are fixed at the time of creation and do not change.

Question 48

Subscriptions

Answer 48

User requests for particular business intelligence results on a stated schedule or in response to particular events.

Question 49

Supervised Data Mining

Answer 49

A form of data mining in which data miners develop a model prior to the analysis and apply statistical techniques to data to estimate values of the parameters of the model.

Question 50

Support

Answer 50

In market-basket terminology, the probability that two items will be purchased together.

Question 51

The Singularity

Answer 51

The point at which computer systems become sophisticated enough that they can create and adapt their own software and hence adapt their behavior without human assistance.

Question 52

Third-Party Cookie

Answer 52

A cookie created by a site other than the one visited.

Question 53

Unsupervised Data Mining

Answer 53

A form of data mining whereby the analysts do not create a model or hypothesis before running the analysis. Instead, they apply the data mining technique to the data and observe the results. With this method, analysts create hypotheses after the analysis to explain the patterns found.