MIS 183 Chapter 10
Which of the following are key steps in a data quality program? A) Conduct a data quality audit B) Apply TQM principles and practices C) Estimate return on investment D) All of the above
D
Which type of index is commonly used in data warehousing environments? A) Join index B) Bit-mapped index C) Secondary index D) Both A and B
D
Informational and operational data differ in all of the following ways EXCEPT: A) level of detail. B) normalization level. C) scope of data. D) data quality.
A
Quality data can be defined as being: A) unique. B) inaccurate. C) historical. D) precise.
A
The major advantage of data propagation is: A) real-time cascading of data changes throughout the organization. B) duplication of non-redundant data. C) the ability to have trickle-feeds. D) none of the above.
A
Which of the following is a basic method for single field transformation? A) Table lookup B) Cross-linking entities C) Cross-linking attributes D) Field-to-field communication
A
________ duplicates data across databases. A) Data propagation B) Data duplication C) Redundant replication D) A replication server
A
) Data governance can be defined as: A) a means to slow down the speed of data. B) high-level organizational groups and processes that oversee data stewardship. C) a government task force for defining data quality. D) none of the above
B
A method of capturing only the changes that have occurred in the source data since the last capture is called ________ extract. A) static B) incremental C) partial D) update-driven
B
All of the following are ways to consolidate data EXCEPT: A) application integration. B) data rollup and integration. C) business process integration. D) user interaction integration.
B
Conformance means that: A) data have been transformed. B) data are stored, exchanged or presented in a format that is specified by its metadata. C) data are stored in a way to expedite retrieval. D) none of the above.
B
Data quality ROI stands for: A) return on investment. B) risk of incarceration. C) rough outline inclusion. D) none of the above
B
Data quality problems can cascade when: A) data are not deleted properly. B) data are copied from legacy systems. C) there is redundant data storage and inconsistent metadata. D) there are data entry problems.
B
Event-drive propagation: A) provides a means to duplicate data for events. B) pushes data to duplicate sites as an event occurs. C) pulls duplicate data from redundant sites. D) none of the above
B
External data sources present problems for data quality because: 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.
B
One simple task of a data quality audit is to: A) interview all users. B) statistically profile all files. C) load all data into a data warehouse. D) establish quality metrics
B
The methods to ensure the quality of data across various subject areas are called: A) Variable Data Management. B) Master Data Management. C) Joint Data Management. D) Managed Data Management.
B
An approach to filling a data warehouse that employs bulk rewriting of the target data periodically is called: A) dump mode. B) overwrite mode. C) refresh mode. D) update mode.
C
Data federation is a technique which: 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
C
Data quality is important for all of the following reasons EXCEPT: 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.
C
In the ________ approach, one consolidated record is maintained and all applications draw on that one actual "golden" record. A) Persistent B) Identity Registry C) Federated D) Integration Hub
C
One way to improve the data capture process is to: A) allow all data to be entered manually. B) provide little or no training to data entry operators. C) check entered data immediately for quality against data in the database. D) not use any automatic data entry routines.
C
The best place to improve data entry across all applications is: A) in the users. B) in the level of organizational commitment. C) in the database definitions. D) in the data entry operators.
C
) TQM stands for: A) Thomas Quinn Mann, a famous data quality innovator. B) Total Quality Manipulation. C) Transforming Quality Management. D) Total Quality Management.
D
A characteristic of reconciled data that means the data reflect an enterprise-wide view is: A) detailed. B) historical. C) normalized. D) comprehensive
D
A technique using artificial intelligence to upgrade the quality of raw data is called: A) dumping. B) data reconciliation. C) completion backwards updates. D) data scrubbing.
D
All of the following are popular architectures for Master Data Management EXCEPT: A) Identity Registry. B) Integration Hub. C) Persistent Object. D) Normalization.
D
All of the following are tasks of data cleansing EXCEPT: A) decoding data to make them understandable for data warehousing applications. B) adding time stamps to distinguish values for the same attribute over time. C) generating primary keys for each row of a table. D) creating foreign keys.
D
Data may be loaded from the staging area into the warehouse by following: A) SQL Commands (Insert/Update). B) special load utilities. C) custom-written routines. D) all of the above.
D
High quality data are data that are: A) accurate. B) consistent. C) available in a timely fashion. D) all of the above.
D
Loading data into a data warehouse involves: A) appending new rows to the tables in the warehouse. B) updating existing rows with new data. C) purging data that have become obsolete or were incorrectly loaded. D) all of the above.
D
One characteristic of quality data which pertains to the expectation for the time between when data are expected and when they are available for use is: A) currency. B) consistency. C) referential Integrity. D) timeliness.
D
The process of combining data from various sources into a single table or view is called: A) extracting. B) updating. C) selecting. D) joining.
D
The process of transforming data from a detailed to a summary level is called: A) extracting. B) updating. C) joining. D) aggregating.
D
