Chapter 9 Quiz STUDY

c. reconciled

Data that are detailed, current, and intended to be the single, authoritative source of all decision support applications are called ________ data. a. detailed b. subject c. reconciled d. derived

d. periodic

Data that are never physically altered once they are added to the store are called ________ data. a. complete b. override c. transient d. periodic

d. surrogate

Every key used to join the fact table with a dimension table should be a ________ key. a. primary b. secondary c. foreign d. surrogate

d. ROLAP tools.

OLAP tools that use the database as a traditional relational database are called: a. TIO tools. b. slice and dice. c. MOLAP tools. d. ROLAP tools.

b. pivoting.

Rotating the view of a multidimensional database for a particular data point is called data: a. drill-down. b. pivoting. c. cubing. d. dicing.

d. NoSQL.

A class of database technology used to store textual and other unstructured data is called: a. KnowSQL. b. mySQL. c. PHP. d. NoSQL.

d. data warehouse that is limited in scope.

A data mart is a(n): a. smaller system built upon file processing technology. b. generic on-line shopping site. c. enterprisewide data warehouse. d. data warehouse that is limited in scope.

d. event.

A database action that results from a transaction is called a(n): a. log entry. b. journal happening. c. transition. d. event.

d. is filled exclusively from the enterprise data warehouse with reconciled data.

A dependent data mart: a. participates in a relationship with an entity. b. is dependent upon an operational system. c. is filled with data extracted directly from the operational system. d. is filled exclusively from the enterprise data warehouse with reconciled data.

d. data mart created by a relational view of a slightly denormalized data warehouse.

A logical data mart is a(n): a. centralized, integrated data warehouse. b. data mart consisting of only logical data. c. integrated, subject-oriented, detailed database designed to serve operational users. d. data mart created by a relational view of a slightly denormalized data warehouse.

a. dimension

A star schema contains both fact and ________ tables. a. dimension b. starter c. cross functional d. narrative

d. it is often more expedient to build a data mart than a data warehouse.

All of the following are limitations of the independent data mart EXCEPT: a. there is no capability to drill down into greater detail in other data marts. b. data marts may not be consistent with one another. c. separate extraction, transformation, and loading processes are developed for each data mart. d. it is often more expedient to build a data mart than a data warehouse.

c. data entry.

All of the following are some beneficial applications for real-time data warehousing EXCEPT: a. just-in-time transportation. b. fraud detection in credit card transactions. c. data entry. d. e-commerce. For example, an abandoned shopping cart can trigger an email promotional message.

b. the process of creating a logical data mart is lengthy.

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 process of creating a logical data mart is lengthy. c. data are moved into the data warehouse rather than a separate staging area. d. the data mart is always up-to-date since data in a view is created when the view is referenced.

a. create a snowflake schema.

All of the following are ways to handle changing dimensions EXCEPT: a. create a snowflake schema. b. for each dimension attribute that changes, create a current value field and as many old value fields as we wish. c. overwrite the current value with the new value. d. create a new dimension table row each time the dimension object changes.

a. integrated, subject-oriented, updateable, current-valued, detailed database designed to serve the decision support needs of operational users.

An operational data store (ODS) is a(n): a. integrated, subject-oriented, updateable, current-valued, detailed database designed to serve the decision support needs of operational users. b. representation of the operational data. c. place to store all unreconciled data. d. small-scale data mart.

c. we are taking inventory of the set of possible occurrences.

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.

c. pivoting.

Going from a summary view to progressively lower levels of detail is called data: a. cubing. b. dicing. c. pivoting. d. drill-down.

d. fact

Grain and duration have a direct impact on the size of ________ tables. a. selection b. figure c. grain d. fact

c. running a business in real time.

Informational systems are designed for all of the following EXCEPT: a. data mining. b. supporting decision making. c. running a business in real time. d. complex queries.

a. the possibility of a new generation of inconsistent data systems, the data marts themselves.

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. denormalized data. c. incongruent data formats. d. lack of user training.

c. A data warehouse centralizes data that are scattered throughout disparate operational systems and makes them readily available for decision support applications.

Operational and informational systems are generally separated because of which of the following factors? a. A separate data warehouse increases contention for resources. b. Only operational systems allow SQL statements. c. A data warehouse centralizes data that are scattered throughout disparate operational systems and makes them readily available for decision support applications. d. A properly designed data warehouse decreases value to data.

d. informational processing.

The analysis of summarized data to support decision making is called: a. data scrubbing. b. artificial intelligence. c. operational processing. d. informational processing.

c. subject-oriented.

The characteristic that indicates that a data warehouse is organized around key high-level entities of the enterprise is: a. integrated. b. time-variant. c. subject-oriented. d. nonvolatile.

a. grain.

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. grain. b. selection. c. span. d. aggregation.

b. Data are immediately transformed and loaded into the warehouse.

The real-time data warehouse is characterized by which of the following? a. It provides periodic access for the transaction processing systems to an enterprise data warehouse. b. Data are immediately transformed and loaded into the warehouse. c. It accepts batch feeds of transaction data. d. It is based on Oracle technology.

c. on-line analytical processing (OLAP).

The use of a set of graphical tools that provides users with multidimensional views of their data is called: a. on-line datacube processing (ODP). b. on-line geometrical processing (OGP). c. on-line analytical processing (OLAP). d. drill-down analysis.

a. determining the number of possible values for each foreign key in the fact table.

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 possible values for each foreign key in the fact table. b. determining the number of DDL statements made to create a table. c. determining the number of TRIGGERS used in the database. d. determining the number of DML statements made to create a table.

a. data in the warehouse contain a time dimension so that they may be used to study trends and changes.

When we consider data in the data warehouse to be time-variant, we mean: a. data in the warehouse contain a time dimension so that they may be used to study trends and changes. b. that time is relative. c. that the time of storage varies. d. that there is a time delay between when data are posted and when we report on the data.

d. Advances in middleware products that enabled enterprise database connectivity across heterogeneous platforms.

Which of the following advances in information systems contributed to the emergence of data warehousing? a. Improvements in monitor technologies. b. The invention of the iPad. c. Increase in viruses and other computer threats. d. Advances in middleware products that enabled enterprise database connectivity across heterogeneous platforms.

b. Target marketing

Which of the following data-mining applications identifies customers for promotional activity? a. Product affinity b. Target marketing c. Population profiling d. Usage analysis

c. Clustering and signal processing

Which of the following data-mining techniques identifies clusters of observations with similar characteristics? a. Rule discovery b. Case reasoning c. Clustering and signal processing d. Neural nets

c. Rule discovery

Which of the following data-mining techniques searches for patterns and correlations in large data sets? a. Neural nets b. Signal processing c. Rule discovery d. Case reasoning

b. Businesses need an integrated view of company information.

Which of the following factors drive the need for data warehousing? a. Reduce virus and Trojan horse threats. b. Businesses need an integrated view of company information. c. Informational data must be kept together with operational data. d. Data warehouses generally have better security.

d. Eliminate the need for application software

Which of the following is NOT an objective of derived data? a. Support data mining applications b. Ease of use for decision support systems c. Faster response time for user queries d. Eliminate the need for application software

a. Correlations and clusters in data can be easily identified.

Which of the following is true of data visualization? a. Correlations and clusters in data can be easily identified. b. It is generally not helpful for decision making. c. It is often used in conjunction with poems. d. It is more difficult to observe trends and patterns in data.

d. Downsizing

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. Focus on supplier relationship management d. Downsizing

b. Big data

________ is an ill-defined term applied to databases where size strains the ability of commonly used relational DBMSs to manage the data. a. Star data b. Big data c. Small data d. Mean data

c. Column databases

________ is/are a new technology which trade(s) off storage space savings for computing time. a. Fact tables b. Snowflake schemas c. Column databases d. Dimensional modeling

d. RFID

________ technologies are allowing more opportunities for real-time data warehouses. a. MOLAP b. Web c. GPS d. RFID