Deck 9: Data Warehousing

Question 1

A data mart is a(n):

A) enterprisewide 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 1

C

Question 2

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.

Answer 2

A

Question 3

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

A) Case reasoning
B) Rule discovery
C) Clustering and signal processing
D) Neural nets

Answer 3

C

Question 4

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

A) Increase in viruses and other computer threats.
B) Improvements in monitor technologies.
C) Advances in middleware products that enabled enterprise database connectivity across heterogeneous platforms.
D) The invention of the iPad.

Question 5

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 6

Which of the following is true of data visualization?

A) It is more difficult to observe trends and patterns in data.
B) Correlations and clusters in data can be easily identified.
C) It is often used in conjunction with poems.
D) It is generally not helpful for decision making.

Question 7

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

A) Case reasoning
B) Rule discovery
C) Signal processing
D) Neural nets

Question 8

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

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

Question 9

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 10

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

A) ROLAP tools.
B) MOLAP tools.
C) slice and dice.
D) TIO tools.

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

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

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

Question 13

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 14

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 15

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 16

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 17

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 18

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 19

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

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

Question 20

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

A) on-line geometrical processing (OGP).
B) drill-down analysis.
C) on-line analytical processing (OLAP).
D) on-line datacube processing (ODP).

Question 21

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 22

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 23

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

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

Question 24

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 25

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 26

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 27

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 28

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 email promotional message.
C) fraud detection in credit card transactions.
D) data entry.

Question 29

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 30

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

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

Question 31

A star schema contains both fact and ________ tables.

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

Question 32

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 33

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 34

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 35

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.

Question 36

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 37

________ 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 38

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

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

Question 39

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

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

Question 40

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 41

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.

Question 42

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

Question 43

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

Question 44

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

Question 45

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

Question 46

Operational metadata are derived from the enterprise data model.

Question 47

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 48

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

Question 49

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 50

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

Question 51

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

Question 52

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.

Question 53

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

Question 54

Scalable technology is critical to a data mart.

Question 55

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

Question 56

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

Question 57

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

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

Question 58

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

Question 59

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

Question 60

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

Question 61

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

Question 62

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

Question 63

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

Question 64

A fact table holds descriptive data about the business.

Question 65

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

Question 66

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

Question 67

A snowflake schema is usually heavily aggregated.

Question 68

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.

Question 69

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

Question 70

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

Question 71

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

Question 72

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

Question 73

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.

Question 74

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

Question 75

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.

Question 76

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

Question 77

Transient data are never changed.

Question 78

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

Question 79

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

Question 80

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