Database Management Chapter 9

Front 1

Going from a summary view to progressively lower levels of detail is called data:

Back 1

drill-down.

Front 2

An enterprise data warehouse is the control point and single source of all data made available to end users for decision support applications.

Back 2

True

Front 3

The need for data warehousing in an organization is driven by its need for an integrated view of high-quality data.

Back 3

True

Front 4

________ is an ill-defined term applied to databases where size strains the ability of commonly used relational DBMSs to manage the data.

Back 4

Big data

Front 5

A dependent data mart is filled from the enterprise data warehouse and its reconciled data.

Back 5

True

Front 6

Which of the following advances in information systems contributed to the emergence of data warehousing?

Back 6

Advances in middleware products that enabled enterprise database connectivity across heterogeneous platforms.

Front 7

When multiple systems in an organization are synchronized, the need for data warehousing increases.

Back 7

False

Front 8

Drill-down involves analyzing a given set of data at a finer level of detail.

Back 8

True

Front 9

A fact table holds descriptive data about the business.

Back 9

False

Front 10

The enterprise data model controls the phased evolution of the data warehouse.

Back 10

True

Front 11

Grain and duration have a direct impact on the size of fact tables.

Back 11

True

Front 12

An operational data store typically holds a history of snapshots of the state of an organization whereas an enterprise data warehouse does not typically contain history.

Back 12

False

Front 13

Rotating the view of a multidimensional database for a particular data point is called data:

Back 13

pivoting

Front 14

An operational data store is typically a relational database and normalized, but it is tuned for decision-making applications.

Back 14

True

Front 15

The use of a set of graphical tools that provides users with multidimensional views of their data is called:

Back 15

on-line analytical processing (OLAP).

Front 16

The grain of a data warehouse indicates the size and depth of the records.

Back 16

False

Front 17

There are applications for fact tables without any nonkey data, only the foreign keys for the associated dimensions.

Back 17

True

Front 18

Which of the following organizational trends does not encourage the need for data warehousing?

Back 18

Downsizing

Front 19

Which of the following data-mining techniques identifies clusters of observations with similar characteristics?

Back 19

Clustering and signal processing

Front 20

Informational systems are designed for all of the following EXCEPT:

Back 20

running a business in real time.

Front 21

Logical data marts are physically separate databases from the enterprise data warehouse.

Back 21

False

Front 22

An event is a database action that results from a transaction.

Back 22

True

Front 23

Data that are detailed, current, and intended to be the single, authoritative source of all decision support applications are called ________ data.

Back 23

reconciled

Front 24

Which of the following is NOT an objective of derived data?

Back 24

Eliminate the need for application software

Front 25

All of the following are some beneficial applications for real-time data warehousing EXCEPT:

Back 25

data entry.

Front 26

Multidimensional OLAP (MOLAP) tools use variations of SQL and view the database as a relational database, in either a star schema or other normalized or denormalized set of tables.

Back 26

False

Front 27

A corporate information factory (CIF) is a comprehensive view of organizational data in support of all user data requirements.

Back 27

True

Front 28

A logical data mart is a(n):

Back 28

data mart created by a relational view of a slightly denormalized data warehouse.

Front 29

Medical claims and pharmaceutical data would be an example of big data.

Back 29

True

Front 30

A dependent data mart:

Back 30

is filled exclusively from the enterprise data warehouse with reconciled data.

Front 31

The first requirement for building a user-friendly interface is a set of metadata that describes the data in the data mart in business terms that users can easily understand.

Back 31

True

Front 32

The development of the relational data model did not contribute to the emergence of data warehousing.

Back 32

False

Front 33

A database action that results from a transaction is called a(n):

Back 33

event

Front 34

An operational data store (ODS) is not designed for use by operational users.

Back 34

False

Front 35

NoSQL is a great technology for storing well-structured data.

Back 35

False

Front 36

Which of the following data-mining techniques searches for patterns and correlations in large data sets?

Back 36

Rule discovery

Front 37

Factless fact tables may apply when:

Back 37

we are deleting correlated data.

Front 38

Conformed dimensions allow users to do the following:

Back 38

query across fact tables with consistency.

Front 39

An operational data store (ODS) is a(n):

Back 39

integrated, subject-oriented, updateable, current-valued, detailed database designed to serve the decision support needs of operational users.

Front 40

All of the following are limitations of the independent data mart EXCEPT:

Back 40

it is often more expedient to build a data mart than a data warehouse.

Front 41

When we consider data in the data warehouse to be time-variant, we mean:

Back 41

data in the warehouse contain a time dimension so that they may be used to study trends and changes.

Front 42

Advances in computer hardware, particularly the emergence of affordable mass storage and parallel computer architectures, was one of the key advances that led to the emergence of data warehousing.

Back 42

True

Front 43

All of the following are unique characteristics of a logical data mart EXCEPT:

Back 43

the process of creating a logical data mart is lengthy.

Front 44

A data mart is a(n):

Back 44

data warehouse that is limited in scope.

Front 45

The real-time data warehouse is characterized by which of the following?

Back 45

Data are immediately transformed and loaded into the warehouse.

Front 46

An independent data mart is filled with data extracted from the operational environment without the benefit of a data warehouse.

Back 46

True

Front 47

The characteristic that indicates that a data warehouse is organized around key high-level entities of the enterprise is:

Back 47

subject-oriented.

Front 48

A snowflake schema is usually heavily aggregated.

Back 48

False

Front 49

Informational systems are designed to support decision making based on historical point-in-time and prediction data.

Back 49

True

Front 50

Data that are never physically altered once they are added to the store are called ________ data.

Back 50

periodic

Front 51

The level of detail in a fact table determined by the intersection of all the components of the primary key, including all foreign keys and any other primary key elements, is called the:

Back 51

grain

Front 52

Every key used to join the fact table with a dimension table should be a ________ key.

Back 52

surrogate

Front 53

A class of database technology used to store textual and other unstructured data is called:

Back 53

NoSQL

Front 54

The analysis of summarized data to support decision making is called:

Back 54

informational processing.

Front 55

Periodic data are data that are never physically altered or deleted once they have been added to the store.

Back 55

True

Front 56

When a dimension participates in a hierarchy, the database designer can normalize the dimension into a nested set of tables with 1:M relationships between them.

Back 56

True

Front 57

Operational metadata are derived from the enterprise data model.

Back 57

False

Front 58

Transient data are never changed.

Back 58

False

Front 59

________ is/are a new technology which trade(s) off storage space savings for computing time.

Back 59

Column databases

Front 60

A star schema contains both fact and ________ tables.

Back 60

dimension

Front 61

A conformed dimension is one or more dimension tables associated with only one fact table.

Back 61

False

Front 62

Organizations adopt data mart architectures because it is easier to have separate, small data warehouses than to get all organizational parties to agree to one view of the organization in a central data warehouse.

Back 62

True

Front 63

A data mart is a data warehouse that contains data that can be used across the entire organization.

Back 63

False

Front 64

An enterprise data warehouse that accepts near-real time feeds of transactional data and immediately transforms and loads the appropriate data is called a real-time data warehouse.

Back 64

True

Front 65

For performance reasons, it may be necessary to define more than one fact table for a star schema.

Back 65

True

Front 66

The status of data is the representation of the data after an event has occurred.

Back 66

False

Front 67

The representation of data in a graphical format is called data mining.

Back 67

False

Front 68

A separate data warehouse causes more contention for resources in an organization.

Back 68

False

Front 69

When determining the size of a fact table, estimating the number of possible values for each dimension associated with the fact table is equivalent to:

Back 69

determining the number of possible values for each foreign key in the fact table.

Front 70

All of the following are ways to handle changing dimensions EXCEPT:

Back 70

create a snowflake schema.

Front 71

Which of the following data-mining applications identifies customers for promotional activity?

Back 71

Target marketing

Front 72

One characteristic of independent data marts is complexity for end users when they need to access data in separate data marts. This complexity is caused by not only having to access data from separate databases, but also from:

Back 72

the possibility of a new generation of inconsistent data systems, the data marts themselves.

Front 73

Operational and informational systems are generally separated because of which of the following factors?

Back 73

A data warehouse centralizes data that are scattered throughout disparate operational systems and makes them readily available for decision support applications.

Front 74

Which of the following factors drive the need for data warehousing?

Back 74

Businesses need an integrated view of company information.

Front 75

Which of the following is true of data visualization?

Back 75

Correlations and clusters in data can be easily identified.

Front 76

Reconciled data are data that have been selected, formatted, and aggregated for end-user decision support applications.

Back 76

False

Front 77

An expanded version of a star schema in which all of the tables are fully normalized is called a(n):

Back 77

snowflake schema.

Front 78

Grain and duration have a direct impact on the size of ________ tables.

Back 78

fact

Front 79

OLAP tools that use the database as a traditional relational database are called:

Back 79

ROLAP tools.

Front 80

________ technologies are allowing more opportunities for real-time data warehouses.

Back 80

RFID

Front 81

Scalable technology is critical to a data mart.

Back 81

True

Front 82

Independent data marts do not generally lead to redundant data and efforts.

Back 82

False

Front 83

Rule discovery searches for patterns and correlations in large data sets.

Back 83

True