Deck 9: Data Warehousing and Data Integration

Question 1

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

A) Web
B) MOLAP
C) RFID
D) GPS

Answer 1

C

Question 2

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

A) It accepts batch feeds of transaction data.
B) Data are immediately transformed and loaded into the warehouse.
C) It provides periodic access for the transaction processing systems to an enterprise data warehouse.
D) It is based on Oracle technology.

Answer 2

B

Question 3

A data mart is a(n):

A) enterprise-wide data warehouse.
B) smaller system built upon file processing technology.
C) data warehouse that is limited in scope.
D) generic on-line shopping site.

Answer 3

C

Question 4

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

A) Multiple, nonsynchronized systems
B) Focus on customer relationship management
C) Downsizing
D) Focus on supplier relationship management

Question 5

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

A) Population profiling
B) Target marketing
C) Usage analysis
D) Product affinity

Question 6

Informational systems are designed for all of the following EXCEPT:

A) running a business in real time.
B) supporting decision making.
C) complex queries.
D) data mining.

Question 7

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:

A) the possibility of a new generation of inconsistent data systems, the data marts themselves.
B) lack of user training.
C) denormalized data.
D) incongruent data formats.

Question 8

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

A) subject-oriented.
B) integrated.
C) time-variant.
D) nonvolatile.

Question 9

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

A) just-in-time transportation.
B) e-commerce. For example, an abandoned shopping cart can trigger an e-mail promotional message.
C) fraud detection in credit card transactions.
D) data entry.

Question 10

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

A) that the time of storage varies.
B) data in the warehouse contain a time dimension so that they may be used to study trends and changes.
C) that there is a time delay between when data are posted and when we report on the data.
D) that time is relative.

Question 11

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

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 12

A dependent data mart:

A) is filled with data extracted directly from the operational system.
B) is filled exclusively from the enterprise data warehouse with reconciled data.
C) is dependent upon an operational system.
D) participates in a relationship with an entity.

Question 13

A logical data mart is a(n):

A) data mart consisting of only logical data.
B) data mart created by a relational view of a slightly denormalized data warehouse.
C) integrated, subject-oriented, detailed database designed to serve operational users.
D) centralized, integrated data warehouse.

Question 14

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

A) logical data marts are not physically separate databases, but rather a relational view of a data warehouse.
B) the data mart is always up-to-date since data in a view is created when the view is referenced.
C) the process of creating a logical data mart is lengthy.
D) data are moved into the data warehouse rather than a separate staging area.

Question 15

The analysis of data or information to support decision making is called:

A) operational processing.
B) informational processing.
C) artificial intelligence.
D) data scrubbing.

Question 16

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

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 17

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

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

Question 18

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

A) Businesses need an integrated view of company information.
B) Informational data must be kept together with operational data.
C) Data warehouses generally have better security.
D) Reduce virus and Trojan horse threats.

Question 19

The key discovery that triggered the development of data warehouses was:

A) computer viruses.
B) new ways to present information using mobile devices.
C) the recognition of the differences between transactional systems and informational systems.
D) the invention of the iPad.

Question 20

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

A) place to store all unreconciled data.
B) representation of the operational data.
C) integrated, subject-oriented, updateable, current-valued, detailed database designed to serve the decision support needs of operational users.
D) small-scale data mart.

Question 21

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:

A) span.
B) grain.
C) selection.
D) aggregation.

Question 22

________ duplicates data across databases.

A) Data propagation
B) Data duplication
C) Redundant replication
D) A replication server

Question 23

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

A) Ease of use for decision support systems
B) Faster response time for user queries
C) Support data mining applications
D) Eliminate the need for application software

Question 24

Factless fact tables may apply when:

A) we are deleting sales.
B) we are tracking sales.
C) we are taking inventory of the set of possible occurrences.
D) we are deleting correlated data.

Question 25

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.

Question 26

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

A) transition.
B) event.
C) log entry.
D) journal happening.

Question 27

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.

Question 28

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

A) mySQL.
B) NoSQL.
C) KnowSQL.
D) PHP.

Question 29

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

A) selection
B) grain
C) fact
D) figure

Question 30

Conformed dimensions allow users to do the following:

A) delete correlated data.
B) query across fact tables with consistency.
C) identify viruses in web sites.
D) fix viruses in html documents.

Question 31

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

A) overwrite the current value with the new value.
B) for each dimension attribute that changes, create a current value field and as many old value fields as we wish.
C) create a new dimension table row each time the dimension object changes.
D) create a snowflake schema.

Question 32

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

A) Dimensional modeling
B) Columnar databases
C) Fact tables
D) Snowflake schemas

Question 33

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

A) Mean data
B) Small data
C) Star data
D) Big data

Question 34

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

A) reconciled
B) subject
C) derived
D) detailed

Question 35

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

A) primary
B) surrogate
C) foreign
D) secondary

Question 36

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

A) transient
B) override
C) periodic
D) complete

Question 37

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:

A) determining the number of DDL statements made to create a table.
B) determining the number of possible values for each foreign key in the fact table.
C) determining the number of DML statements made to create a table.
D) determining the number of TRIGGERS used in the database.

Question 38

A star schema contains both fact and ________ tables.

A) narrative
B) cross functional
C) dimension
D) starter

Question 39

Event-driven 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) triggers a virus.

Question 40

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

A) snowflake schema.
B) operational schema.
C) DSS schema.
D) complete schema.

Question 41

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

Question 42

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.

Question 43

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

Question 44

The process of combining data from various sources into a single table or view is called:

A) extracting.
B) updating.
C) selecting.
D) joining.

Question 45

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.

Question 46

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

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

Question 47

Which type of index is commonly used in data warehousing environments?

A) Joint index
B) Bitmapped index
C) Secondary index
D) Tri-dex

Question 48

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.

Question 49

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.

Question 50

A characteristic of reconciled data that means the data reflect an enterprise-wide view is:

A) detailed.
B) historical.
C) normalized.
D) comprehensive.

Question 51

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) virus elimination.

Question 52

The process of transforming data from a detailed to a summary level is called:

A) extracting.
B) updating.
C) joining.
D) aggregating.

Question 53

User interaction integration is achieved by creating fewer ________ that feed different systems.

A) clients
B) networks
C) computers
D) user interfaces

Question 54

Loading data into a data warehouse does NOT involve:

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) formatting the hard drive.

Question 55

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

Question 56

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

Question 57

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

Question 58

Data may be loaded from the staging area into the warehouse by following:

A) SQL commands (Insert/Update).
B) SQL purge.
C) custom-written letters.
D) virus checking.

Question 59

A technique using pattern recognition to upgrade the quality of raw data is called:

A) data scrounging.
B) data scrubbing.
C) data gouging.
D) data analysis.

Question 60

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

Question 61

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

Question 62

Scalable technology is often critical to a data mart.

Question 63

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

Question 64

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

Question 65

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

Question 66

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

Question 67

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

Question 68

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

Question 69

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.

Question 70

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

Question 71

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

Question 72

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

Question 73

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

Question 74

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

Question 75

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

Question 76

Operational metadata are derived from the enterprise data model.

Question 77

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

Question 78

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

Question 79

Transient data are never changed.

Question 80

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.