Question 1

Data federation is a technique which:

Accepted Answer

A)  creates an integrated database from several separate databases. 
B)  creates a distributed database. 
C)  provides a virtual view of integrated data without actually creating one centralized database. 
D)  provides a real-time update of shared data. 
A)  creates an integrated database from several separate databases. 
B)  creates a distributed database. 
C)  provides a virtual view of integrated data without actually creating one centralized database. 
D)  provides a real-time update of shared data.

Question 2

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.

Accepted Answer

A) True 
 B)False

Question 3

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

Accepted Answer

A)  cubing. 
B)  drill down. 
C)  dicing. 
D)  pivoting. 
A)  cubing. 
B)  drill down. 
C)  dicing. 
D)  pivoting.

Question 4

What is a field-level transformation, and what different types exist?

Accepted Answer

A field-level function converts data fro

Question 5

A method of capturing only the changes that have occurred in the source data since the last capture is called ________ extract.

Accepted Answer

A)  static 
B)  incremental 
C)  partial 
D)  update-driven 
A)  static 
B)  incremental 
C)  partial 
D)  update-driven

Question 6

What is the surrogate key rule for the star schema, and what are the main reasons for this rule?

Accepted Answer

Each and every key used to join the fact

Question 7

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.

Accepted Answer

A) True 
 B)False

Question 8

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

Accepted Answer

A) True 
 B)False

Question 9

Operational metadata are derived from the enterprise data model.

Accepted Answer

A) True 
 B)False

Question 10

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

Accepted Answer

A)  separate extraction, transformation, and loading processes are developed for each data mart. 
B)  data marts may not be consistent with one another. 
C)  there is no capability to drill down into greater detail in other data marts. 
D)  it is often more expedient to build a data mart than a data warehouse. 
A)  separate extraction, transformation, and loading processes are developed for each data mart. 
B)  data marts may not be consistent with one another. 
C)  there is no capability to drill down into greater detail in other data marts. 
D)  it is often more expedient to build a data mart than a data warehouse.

Question 11

The process of transforming data from detailed to summary levels is called normalization.

Accepted Answer

A) True 
 B)False

Question 12

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

Accepted Answer

A) True 
 B)False

Question 13

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.

Accepted Answer

A) True 
 B)False

Question 14

What are some of the errors and inconsistencies in data that the cleansing process is looking to rectify?

Accepted Answer

There are many errors and inconsistencie

Question 15

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

Accepted Answer

A)  A data warehouse centralizes data that are scattered throughout disparate operational systems and makes them readily available for decision support applications. 
B)  A properly designed data warehouse decreases value to data. 
C)  A separate data warehouse increases contention for resources. 
D)  Only operational systems allow SQL statements. 
A)  A data warehouse centralizes data that are scattered throughout disparate operational systems and makes them readily available for decision support applications. 
B)  A properly designed data warehouse decreases value to data. 
C)  A separate data warehouse increases contention for resources. 
D)  Only operational systems allow SQL statements.

Question 16

Converting data from the format of its source to the format of its destination is called:

Accepted Answer

A)  data transformation. 
B)  data loading. 
C)  data scrubbing. 
D)  data storage. 
A)  data transformation. 
B)  data loading. 
C)  data scrubbing. 
D)  data storage.

Question 17

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

Accepted Answer

A) True 
 B)False

Question 18

What is the difference between an incremental extract and a static extract?

Accepted Answer

A static extract captures a sn

Question 19

The major advantage of data propagation is:

Accepted Answer

A)  real-time cascading of data changes throughout the organization. 
B)  duplication of non-redundant data. 
C)  the ability to have trickle-feeds. 
D)  virus elimination. 
A)  real-time cascading of data changes throughout the organization. 
B)  duplication of non-redundant data. 
C)  the ability to have trickle-feeds. 
D)  virus elimination.

Question 20

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

Accepted Answer

A) True 
 B)False

Data federation is a technique which:

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.

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

What is a field-level transformation, and what different types exist?

A method of capturing only the changes that have occurred in the source data since the last capture is called ________ extract.

What is the surrogate key rule for the star schema, and what are the main reasons for this rule?

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.

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

Operational metadata are derived from the enterprise data model.

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

The process of transforming data from detailed to summary levels is called normalization.

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

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.

What are some of the errors and inconsistencies in data that the cleansing process is looking to rectify?

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

Converting data from the format of its source to the format of its destination is called:

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

What is the difference between an incremental extract and a static extract?

The major advantage of data propagation is:

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

The Database Environment and Development Process

Modeling Data in the Organization

The Enhanced E-R Model

Logical Database Design and the Relational Model

Introduction to SQL

Advanced SQL

Databases in Applications

Physical Database Design and Database Infrastructure

Big Data Technologies

Analytics and Its Implications

Data and Database Administration With Focus on Data Quality

Distributed Databases

Object-Oriented Data Modeling

Filters

Exam 9: Data Warehousing and Data Integration

Data federation is a technique which:

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.

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

What is a field-level transformation, and what different types exist?

A method of capturing only the changes that have occurred in the source data since the last capture is called ________ extract.

What is the surrogate key rule for the star schema, and what are the main reasons for this rule?

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.

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

Operational metadata are derived from the enterprise data model.

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

The process of transforming data from detailed to summary levels is called normalization.

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

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.

What are some of the errors and inconsistencies in data that the cleansing process is looking to rectify?

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

Converting data from the format of its source to the format of its destination is called:

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

What is the difference between an incremental extract and a static extract?

The major advantage of data propagation is:

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

The Database Environment and Development Process

Modeling Data in the Organization

The Enhanced E-R Model

Logical Database Design and the Relational Model

Introduction to SQL

Advanced SQL

Databases in Applications

Physical Database Design and Database Infrastructure

Big Data Technologies

Analytics and Its Implications

Data and Database Administration With Focus on Data Quality

Distributed Databases

Object-Oriented Data Modeling

Filters