Chapter 9 Quiz
34) OLAP tools that use the database as a traditional relational database are called 1.A) ROLAP tools. 2.B) MOLAP tools. 3.C) slice and dice. 4.D) none of the above.
A
5) Which of the following factors drive the need for data warehousing 1.A) Businesses need an integrated view of company information. 2.B) Informational data must be kept together with operational data. 3.C) Data warehouses generally have better security. 4.D) None of the above.
A
7) Informational systems are designed for all of the following EXCEPT 1.A) running a business in real time. 2.B) supporting decision making. 3.C) complex queries. 4.D) data mining.
A
6) Which of the following organizational trends does not encourage the need for data warehousing 1.A) Multiple, nonsynchronized systems 2.B) Focus on customer relationship management 3.C) Downsizing 4.D) Focus on supplier relationship management
C
66) Transient data are never changed
FALSE
79) Rule discovery searches for patterns and correlations in large data sets
TRUE
10) 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 1.A) the possibility of a new generation of inconsistent data systems, the data marts themselves. 2.B) lack of user training. 3.C) denormalized data. 4.D) incongruent data formats.
A
1) The analysis of summarized data to support decision making is called 1. A) operational processing. 2. B) informational processing. 3. C) artificial intelligence. 4. D) data scrubbing.
B
12) A dependent data mart 1.A) is filled with data extracted directly from the operational system. 2.B) is filled exclusively from the enterprise data warehouse with reconciled data. 3.C) is dependent upon an operational system. 4.D) participates in a relationship with an entity.
B
14) A logical data mart is a(n) 1.A) data mart consisting of only logical data. 2.B) data mart created by a relational view of a slightly denormalized data warehouse. 3.C) integrated, subject-oriented, detailed database designed to serve operational users. 4.D) centralized, integrated data warehouse.
B
15) All of the following are unique characteristics of a logical data mart EXCEPT 1.A) logical data marts are not physically separate databases, but rather a relational view of a data warehouse. 2.B) the data mart is always up-to-date since data in a view is created when the view is referenced. 3.C) the process of creating a logical data mart is lengthy. 4.D) data are moved into the data warehouse rather than a separate staging area.
C
17) ________ technologies are allowing more opportunities for real-time data warehouses 1.A) Web 2.B) MOLAP 3.C) RFID 4.D) GPS
C
23) A star schema contains both fact and ________ tables. 1.A) narrative 2.B) cross functional 3.C) dimension 4.D) starter
C
11) All of the following are limitations of the independent data mart EXCEPT 1.A) separate extraction, transformation, and loading processes are developed for each data mart. 2.B) data marts may not be consistent with one another. 3.C) there is no capability to drill down into greater detail in other data marts. 4.D) it is often more expedient to build a data mart than a data warehouse.
D
18) All of the following are some beneficial applications for real-time data warehousing EXCEPT 1.A) just-in-time transportation. 2.B) e-commerce. For example, an abandoned shopping cart can trigger an email promotional message. 3.C) fraud detection in credit card transactions. 4.D) data entry.
D
42) The development of the relational data model did not contribute to the emergence of data warehousing
FALSE
44) When multiple systems in an organization are synchronized, the need for data warehousing increases
FALSE
46) A separate data warehouse causes more contention for resources in an organization
FALSE
48) A data mart is a data warehouse that contains data that can be used across the entire organization
FALSE
50) Independent data marts do not generally lead to redundant data and efforts
FALSE
53) An operational data store (ODS) is not designed for use by operational users
FALSE
55) 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
FALSE
57) Logical data marts are physically separate databases from the enterprise data warehouse
FALSE
60) Reconciled data are data that have been selected, formatted, and aggregated for end-user decision support applications
FALSE
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
TRUE
43) The need for data warehousing in an organization is driven by its need for an integrated view of high-quality data
TRUE
45) Informational systems are designed to support decision making based on historical point-in-time and prediction data
TRUE
47) An independent data mart is filled with data extracted from the operational environment without the benefit of a data warehouse
TRUE
49) 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
TRUE
51) An enterprise data warehouse is the control point and single source of all data made available to end users for decision support applications
TRUE
52) A dependent data mart is filled from the enterprise data warehouse and its reconciled data
TRUE
54) An operational data store is typically a relational database and normalized, but it is tuned for decision-making applications
TRUE
56) A corporate information factory (CIF) is a comprehensive view of organizational data in support of all user data requirements
TRUE
58) Scalable technology is critical to a data mart
TRUE
59) 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
TRUE
61) The enterprise data model controls the phased evolution of the data warehouse
TRUE
63) An event is a database action that results from a transaction
TRUE
65) Periodic data are data that are never physically altered or deleted once they have been added to the store
TRUE
69) For performance reasons, it may be necessary to define more than one fact table for a star schema
TRUE
70) There are applications for fact tables without any nonkey data, only the foreign keys for the associated dimensions
TRUE
72) 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
TRUE
35) Rotating the view of a multidimensional database for a particular data point is called data 1.A) cubing. 2.B) drill-down. 3.C) dicing. 4.D) pivoting.
D
80) The representation of data in a graphical format is called data mining
FALSE
19) Data that are detailed, current, and intended to be the single, authoritative source of all decision support applications are called ________ data. 1.A) reconciled 2.B) subject 3.C) derived 4.D) detailed
A
2) The characteristic that indicates that a data warehouse is organized around key high-level entities of the enterprise is 1. A) Subject-oriented 2. B) integrated. 3. C) time-variant. 4. D) nonvolatile.
A
28) An expanded version of a star schema in which all of the tables are fully normalized is called a(n) 1.A) snowflake schema. 2.B) operational schema. 3.C) DSS schema. 4.D) complete schema.
A
20) A database action that results from a transaction is called a(n) 1.A) transition. 2.B) event. 3.C) log entry. 4.D) journal happening.
B
24) Every key used to join the fact table with a dimension table should be a ________ key. 1.A) primary 2.B) surrogate 3.C) foreign 4.D) secondary
B
25) 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 1.A) span. 2.B) grain. 3.C) selection. 4.D) aggregation.
B
3) When we consider data in the data warehouse to be time-variant, we mean 1. A) that the time of storage varies. 2. B) data in the warehouse contain a time dimension so that they may be used to study trends and changes. 3. C) that there is a time delay between when data are posted and when we report on the data. 4. D) none of the above.
B
31) ________ is/are a new technology which trade(s) off storage space savings for computing time. 1.A) Dimensional modeling 2.B) Column databases 3.C) Fact tables 4.D) Snowflake schemas
B
37) Going from a summary view to progressively lower levels of detail is called data 1.A) cubing. 2.B) drill-down. 3.C) dicing. 4.D) pivoting.
B
39) Which of the following data-mining techniques searches for patterns and correlations in large data sets? 1.A) Case reasoning 2.B) Rule discovery 3.C) Signal processing 4.D) Neural nets
B
40) Which of the following data-mining applications identifies customers for promotional activity? 1.A) Population profiling 2.B) Target marketing 3.C) Usage analysis 4.D) Product affinity
B
32) A class of database technology used to store textual and other unstructured data is called 1.A) mySQL. 2.B) NoSQL. 3.C) KnowSQL. 4.D) PHP
B .
21) Data that are never physically altered once they are added to the store are called ________ data. 1.A) transient 2.B) override 3.C) periodic 4.D) complete
C
33) The use of a set of graphical tools that provides users with multidimensional views of their data is called 1.A) on-line geometrical processing (OGP). 2.B) drill-down analysis. 3.C) on-line analytical processing (OLAP). 4.D) on-line datacube processing (ODP).
C
38) Which of the following data-mining techniques identifies clusters of observations with similar characteristics? 1.A) Case reasoning 2.B) Rule discovery 3.C) Clustering and signal processing 4.D) Neural nets
C
9) A data mart is a(n) 1.A) enterprisewide data warehouse. 2.B) smaller system built upon file processing technology. 3.C) data warehouse that is limited in scope. 4.D) generic on-line shopping site.
C
13) An operational data store (ODS) is a(n) 1.A) place to store all unreconciled data. 2.B) representation of the operational data. 3.C) integrated, subject-oriented, updateable, current-valued, detailed database designed to serve the decision support needs of operational users. 4.D) small-scale data mart
C .
22) Which of the following is an objective of derived data? 1.A) ease of use for decision support systems 2.B) faster response time for user queries 3.C) support data mining applications 4.D) All of the above
D
26) Conformed dimensions allow users to do the following 1.A) share nonkey dimension data. 2.B) query across fact tables with consistency. 3.C) work on facts and business subjects for which all users have the same meaning. 4.D) all of the above.
D
27) Factless fact tables may apply when 1.A) we are tracking events. 2.B) we are tracking sales. 3.C) we are taking inventory of the set of possible occurrences. 4.D) both A and C.
D
29) All of the following are ways to handle changing dimensions EXCEPT 1.A) overwrite the current value with the new value. 2.B) for each dimension attribute that changes, create a current value field and as many old value fields as we wish. 3.C) create a new dimension table row each time the dimension object changes. 4.D) create a snowflake schema.
D
30) ________ is an ill-defined term applied to databases where size strains the ability of commonly used relational DBMSs to manage the data. 1.A) Mean data 2.B) Small data 3.C) Star data 4.D) Big data
D
36) Which of the following is true of data visualization? 1.A) It is easier to observe trends and patterns in data. 2.B) Correlations and clusters in data can be easily identified. 3.C) It is often used in conjunction with data mining. 4.D) All of the above
D
4) Which of the following advances in information systems contributed to the emergence of data warehousing 1.A) Improvements in database technology, particularly the relational data model 2.B) Advances in computer hardware, especially affordable mass storage and parallel computer architectures 3.C) Advances in middleware products that enabled enterprise database connectivity across heterogeneous platforms 4.D) All of the above
D
8) Operational and informational systems are generally separated because of which of the following factors 1.A) A data warehouse centralizes data that are scattered throughout disparate operational systems and makes them readily available for decision support applications. 2.B) A properly designed data warehouse adds value to data by improving their quality and consistency. 3.C) A separate data warehouse eliminates contention for resources that results when informational applications are confounded with operational processing. 4.D) All of the above.
D
16) The real-time data warehouse is characterized by which of the following 1.A) It accepts near-real time feeds of transaction data. 2.B) Data are immediately transformed and loaded into the warehouse. 3.C) It provides near-real-time access for the transaction processing systems to an enterprise data warehouse. 4.D) All of the above
D .
62) Operational metadata are derived from the enterprise data model
FALSE
64) The status of data is the representation of the data after an event has occurred
FALSE
67) A fact table holds descriptive data about the business
FALSE
68) The grain of a data warehouse indicates the size and depth of the records
FALSE
71) A conformed dimension is one or more dimension tables associated with only one fact table
FALSE
73) A snowflake schema is usually heavily aggregated
FALSE
75) NoSQL is a great technology for storing well-structured data
FALSE
77) 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
FALSE
74) Medical claims and pharmaceutical data would be an example of big data
TRUE
76) The first requirement for building a user-friendly interface is a set of metadata that describes the data in the data mart in business terms that users can easily understand
TRUE
78) Drill-down involves analyzing a given set of data at a finer level of detail
TRUE
