Question 1

Why is data quality important?

Accepted Answer

Data quality is important to minimize IT

Question 2

Getting poor data from a supplier is a(n) ________ reason for deteriorated data quality.

Accepted Answer

A)  external data source. 
B)  inconsistent metadata 
C)  data entry problem 
D)  lack of organizational commitment 
A)  external data source. 
B)  inconsistent metadata 
C)  data entry problem 
D)  lack of organizational commitment

Question 3

Retention refers to the amount of data that is not purged periodically from tables.

Accepted Answer

A) True 
 B)False

Question 4

Discuss data governance and what needs to be included in a data governance program.

Accepted Answer

Data governance is a set of processes an

Question 5

External data sources present problems for data quality because:

Accepted Answer

A)  data are not always available. 
B)  there is a lack of control over data quality. 
C)  there are poor data capture controls. 
D)  data are unformatted. 
A)  data are not always available. 
B)  there is a lack of control over data quality. 
C)  there are poor data capture controls. 
D)  data are unformatted.

Question 6

There are six major steps to ETL.

Accepted Answer

A) True 
 B)False

Question 7

All of the following are ways to consolidate data EXCEPT:

Accepted Answer

A)  application integration. 
B)  data rollup and integration. 
C)  business process integration. 
D)  user interaction integration. 
A)  application integration. 
B)  data rollup and integration. 
C)  business process integration. 
D)  user interaction integration.

Question 8

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 9

Master data management is the disciplines, technologies and methods to ensure the currency, meaning and quality of data within one subject area.

Accepted Answer

A) True 
 B)False

Question 10

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 11

Data quality is important for all of the following reasons EXCEPT:

Accepted Answer

A)  it minimizes project delay. 
B)  it aids in making timely business decisions. 
C)  it provides a stream of profit. 
D)  it helps to expand the customer base. 
A)  it minimizes project delay. 
B)  it aids in making timely business decisions. 
C)  it provides a stream of profit. 
D)  it helps to expand the customer base.

Question 12

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 13

Joining is often complicated by problems such as errors in source data.

Accepted Answer

A) True 
 B)False

Question 14

User interaction integration is achieved by creating fewer user interfaces.

Accepted Answer

A) True 
 B)False

Question 15

What are some of the characteristics of quality data?

Accepted Answer

There are many characteristics that defi

Question 16

Lack of organizational commitment is a potential reason for an organizations deteriorated data quality.

Accepted Answer

A) True 
 B)False

Question 17

Data quality is essential for SOX and Basel II compliance.

Accepted Answer

A) True 
 B)False

Question 18

Informational and operational data differ in all of the following ways EXCEPT:

Accepted Answer

A)  level of detail. 
B)  normalization level. 
C)  scope of data. 
D)  data quality. 
A)  level of detail. 
B)  normalization level. 
C)  scope of data. 
D)  data quality.

Question 19

A data stewardship program does not help to involve the organization in data quality.

Accepted Answer

A) True 
 B)False

Question 20

Including data capture controls (i.e., dropdown lists) helps reduce ________ deteriorated data problems.

Accepted Answer

A)  external data source 
B)  inconsistent metadata 
C)  data entry 
D)  lack of organizational commitment 
A)  external data source 
B)  inconsistent metadata 
C)  data entry 
D)  lack of organizational commitment

Why is data quality important?

Getting poor data from a supplier is a(n) ________ reason for deteriorated data quality.

Retention refers to the amount of data that is not purged periodically from tables.

Discuss data governance and what needs to be included in a data governance program.

External data sources present problems for data quality because:

There are six major steps to ETL.

All of the following are ways to consolidate data EXCEPT:

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

Master data management is the disciplines, technologies and methods to ensure the currency, meaning and quality of data within one subject area.

The major advantage of data propagation is:

Data quality is important for all of the following reasons EXCEPT:

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

Joining is often complicated by problems such as errors in source data.

User interaction integration is achieved by creating fewer user interfaces.

What are some of the characteristics of quality data?

Lack of organizational commitment is a potential reason for an organizations deteriorated data quality.

Data quality is essential for SOX and Basel II compliance.

Informational and operational data differ in all of the following ways EXCEPT:

A data stewardship program does not help to involve the organization in data quality.

Including data capture controls (i.e., dropdown lists) helps reduce ________ deteriorated data problems.

The Database Environment and Development Process

Modeling Data in the Organization

The Enhanced E-R Model

Logical Database Design and the Relational Model

Physical Database Design and Performance

Introduction to SQL

Advanced SQL

Database Application Development

Data Warehousing

Big Data and Analytics

Data and Database Administration

Distributed Databases

Object-Oriented Data Modeling

Filters

Exam 10: Data Quality and Integration

Why is data quality important?

Getting poor data from a supplier is a(n) ________ reason for deteriorated data quality.

Retention refers to the amount of data that is not purged periodically from tables.

Discuss data governance and what needs to be included in a data governance program.

External data sources present problems for data quality because:

There are six major steps to ETL.

All of the following are ways to consolidate data EXCEPT:

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

Master data management is the disciplines, technologies and methods to ensure the currency, meaning and quality of data within one subject area.

The major advantage of data propagation is:

Data quality is important for all of the following reasons EXCEPT:

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

Joining is often complicated by problems such as errors in source data.

User interaction integration is achieved by creating fewer user interfaces.

What are some of the characteristics of quality data?

Lack of organizational commitment is a potential reason for an organizations deteriorated data quality.

Data quality is essential for SOX and Basel II compliance.

Informational and operational data differ in all of the following ways EXCEPT:

A data stewardship program does not help to involve the organization in data quality.

Including data capture controls (i.e., dropdown lists) helps reduce ________ deteriorated data problems.

The Database Environment and Development Process

Modeling Data in the Organization

The Enhanced E-R Model

Logical Database Design and the Relational Model

Physical Database Design and Performance

Introduction to SQL

Advanced SQL

Database Application Development

Data Warehousing

Big Data and Analytics

Data and Database Administration

Distributed Databases

Object-Oriented Data Modeling

Filters