Management Information Systems, 12e (Laudon) Chapter 6 Foundations of Business Intelligence: Databases and Information anagement
1) A grouping of characters into a word, a group of words, or a complete number is called a record. Answer: FALSE Diff: 1 age !ef: "1# AA$S%: &se of '( $ASE: $ontent b*ecti+e: .") Each characteristic or ualit/ describing a particular entit/ is called an attribute. Answer: (!&E Diff: 1 age !ef: "1# AA$S%: &se of '( $ASE: $ontent b*ecti+e: .-) Program-data -) Program-data dependence refers to the coupling of data stored in files and software programs that use this data such that changes chang es in programs reuire changes to the data. Answer: (!&E Diff: " age !ef: "11 AA$S%: &se of '( $ASE: $ontent b*ecti+e: .1 0) A D%S separates the logical and ph/sical +iews of data. Answer: (!&E Diff: " age !ef: "1" AA$S%: &se of '( $ASE: $ontent b*ecti+e: ." 2) E+er/ record in a file should shou ld contain at least one 3e/ field. Answer: (!&E Diff: 1 age !ef: "10 AA$S%: &se of '( $ASE: $ontent b*ecti+e: .) an/ applications toda/ reuire databases that can store and retrie+e multimedia. Answer: (!&E Diff: 1 age !ef: "12 AA$S%: &se of '( $ASE: $ontent b*ecti+e: ."
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4) ne of the drawbac3s to D%S are that the/ cannot wor3 with applets. Answer: FALSE Diff: " age !ef: "12 AA$S%: &se of '( $ASE: $ontent b*ecti+e: ." 5) D%S are slower than relational D%S. Answer: (!&E Diff: " age !ef: "12 AA$S%: &se of '( $ASE: $ontent b*ecti+e: ." 6) A data dictionar/ is a language associated with a database management manage ment s/stem that end users and programmers use to manipulate data in the database. Answer: FALSE Diff: 1 age !ef: "14 AA$S%: &se of '( $ASE: $ontent b*ecti+e: ." 1#) 'n a relational database, comple7 groupings of data must be streamlined to eliminate aw3ward man/8to8man/ relationships. Answer: (!&E Diff: 1 age !ef: ""# AA$S%: &se of '( $ASE: $ontent b*ecti+e: .11) A data warehouse ma/ be updated b/ a legac/ s/stem. Answer: (!&E Diff: 1 age !ef: """ AA$S%: &se of '( $ASE: $ontent b*ecti+e: .0 1") A data warehouse is t/picall/ comprised c omprised of se+eral smaller data marts. Answer: FALSE Diff: " age !ef: ""AA$S%: &se of '( $ASE: $ontent b*ecti+e: .0
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1-) LA is a 3e/ tool of %'. Answer: (!&E Diff: " age !ef: ""0 AA$S%: &se of '( $ASE: $ontent b*ecti+e: .0 10) LA enables users to obtain online answers to ad8hoc uestions in a fairl/ rapid amount of time, e7cept when the data are stored in +er/ large databases. Answer: FALSE Diff: " age !ef: ""0 AA$S%: &se of '( $ASE: $ontent b*ecti+e: .0 12) redicti+e anal/sis is s/non/mous with data mining. Answer: FALSE Diff: age !ef: "" AA$S%: &se of '( $ASE: $ontent b*ecti+e: .0 1) 'n a 9eb8based database, middleware is used to transfer information from the organiation;s internal database bac3 to the 9eb ser+er for deli+er/ in the form of a 9eb page to the user. Answer: (!&E Diff: " age !ef: ""6 AA$S%: &se of '( $ASE: $ontent b*ecti+e: .0 14) (he disad+antage of using a 9eb interface for a database is that it t/picall/ reuires substantial changes to the internal database. Answer: FALSE Diff: 1 age !ef: ""6 AA$S%: &se of '( $ASE: $ontent b*ecti+e: .0 15) $ommon
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16) Data administration is a special organiational function that manag es the policies and procedures through which data can be managed as an organiational resource. Answer: (!&E Diff: " age !ef: "-# AA$S%: &se of '( $ASE: $ontent b*ecti+e: .2 "#) Data cleansing is the same process as data scrubbing. Answer: (!&E Diff: 1 age !ef: "-1 AA$S%: &se of '( $ASE: $ontent b*ecti+e: .2 "1) 9hich of the following best illustrates the relationship between entities and attributes= A) the entit/ $&S(E! with the attribute !D&$( %) the entit/ $&S(E! with the attribute &!$>ASE $) the entit/ !D&$( with the attribute &!$>ASE D) the entit/ !D&$( with the attribute $&S(E! Answer: % Diff: age !ef: "1# AA$S%: Anal/tic S3ills $ASE: Anal/sis b*ecti+e: ."") 9hich of the following is not one of the main problems with a traditional file en+ironment= A) data inconsistenc/ %) program8data independence $) lac3 of fle7ibilit/ in creating ad8hoc reports D) poor securit/ Answer: % Diff: " age !ef: "11 AA$S%: &se of '( $ASE: Anal/sis b*ecti+e: .1 "-) A D%S reduces data redundanc/ and inconsistenc/ b/ A) enforcing referential integrit/. %) uncoupling program and data. $) utiliing a data dictionar/. D) minimiing isolated files with repeated data. Answer: D Diff: age !ef: "1AA$S%: &se of '( $ASE: $ontent b*ecti+e: .1 0 Copyright © 2012 Pearson Education, Inc.
"0) A characteristic or ualit/ describing an entit/ is called a?n) A) field. %) tuple. $) 3e/ field. D) attribute. Answer: D Diff: 1 age !ef: "1# AA$S%: &se of '( $ASE: $ontent b*ecti+e: ."2) 9hich of the following non8digital data storage items is most similar to a database= A) librar/ card catalog %) cash register receipt $) doctor;s office in+oice D) list of sales totals on a spreadsheet Answer: A Diff: " age !ef: "1#8"11 AA$S%: Anal/tic S3ills $ASE: Anal/sis b*ecti+e: .1 ") (he confusion created b/ @@@@@@@@ ma3es it difficult for companies to create customer relationship management, suppl/ chain management, or enterprise s/stems that integrate data from different sources. A) batch processing %) data redundanc/ $) data independence D) online processing Answer: % Diff: 1 age !ef: "11 AA$S%: &se of '( $ASE: $ontent b*ecti+e: .1 "4) Duplicate data in multiple data files is called data @@@@@@@@. A) redundanc/ %) repetition $) independence D) partitions Answer: A Diff: 1 age !ef: "11 AA$S%: &se of '( $ASE: $ontent b*ecti+e: .1
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"5) A D%S ma3es the A) ph/sical database a+ailable for different logical +iews. %) logical database a+ailable for different anal/tical +iews. $) ph/sical database a+ailable for different anal/tical +iews. D) logical database a+ailable for different ph/sical +iews. Answer: A Diff: " age !ef: "1" AA$S%: &se of '( $ASE: $ontent b*ecti+e: ." "6) (he logical +iew A) shows how data are organied and structured on the storage media. %) presents an entr/ screen to the user. $) allows the creation of supplementar/ reports. D) presents data as the/ would be percei+ed b/ end users. Answer: D Diff: " age !ef: "1" AA$S%: &se of '( $ASE: $ontent b*ecti+e: ." -#) D%S for midrange computers include all of the following E$E( A) D%". %) racle. $) icrosoft SBL Ser+er. D) icrosoft Access. Answer: D Diff: age !ef: "1AA$S%: &se of '( $ASE: $ontent b*ecti+e: ." -1) (he t/pe of logical database model that treats data as if the/ were stored in two8dimensional tables is the A) D%S. %) pre8digital D%S. $) relational D%S. D) hierarchical D%S. Answer: $ Diff: 1 age !ef: "1AA$S%: &se of '( $ASE: $ontent b*ecti+e: ."
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-") racle Database Lite is a?n) A) D%S for small handheld computing de+ices. %) 'nternet D%S. $) mainframe relational D%S. D) D%S for midrange computers. Answer: A Diff: age !ef: "1AA$S%: &se of '( $ASE: $ontent b*ecti+e: ." --) icrosoft SBL Ser+er is a?n) A) D%S for small handheld computing de+ices. %) 'nternet D%S. $) des3top relational D%S. D) D%S for midrange computers. Answer: D Diff: age !ef: "1AA$S%: &se of '( $ASE: $ontent b*ecti+e: ." -0) 'n a table for customers, the information about a single customer would reside in a single A) field. %) row. $) column. D) table. Answer: % Diff: 1 age !ef: "10 AA$S%: &se of '( $ASE: Anal/sis b*ecti+e: .-2) 'n a relational database, a record is referred to in technical terms as a?n) A) tuple. %) row. $) entit/. D) field. Answer: A Diff: " age !ef: "10 AA$S%: &se of '( $ASE: $ontent b*ecti+e: .-
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-) A field identified in a table as holding the uniue identifier of the table;s records is called the A) primar/ 3e/. %) 3e/ field. $) primar/ field. D) uniue 'D. Answer: A Diff: " age !ef: "10 AA$S%: &se of '( $ASE: $ontent b*ecti+e: .-4) A field identified in a record as holding the uniue identifier for that record is called the A) primar/ 3e/. %) 3e/ field. $) primar/ field. D) uniue 'D. Answer: % Diff: " age !ef: "10 AA$S%: &se of '( $ASE: $ontent b*ecti+e: .-5) 'n a relational database, the three basic operations used to de+elop useful sets of data are A) select, pro*ect, and where. %) select, *oin, and where. $) select, pro*ect, and *oin. D) select, from, and *oin. Answer: $ Diff: " age !ef: "12 AA$S%: &se of '( $ASE: $ontent b*ecti+e: .-6) (he select operation A) combines relational tables to pro+ide the user with more information than is otherwise a+ailable. %) creates a subset consisting of columns in a table. $) identifies the table from which the columns will be selected. D) creates a subset consisting of all records in the file that meet stated criteria. Answer: D Diff: 1 age !ef: "12 AA$S%: &se of '( $ASE: $ontent b*ecti+e: .-
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0#) (he join operation A) combines relational tables to pro+ide the user with more information than is otherwise a+ailable. %) identifies the table from which the columns will be selected. $) creates a subset consisting of columns in a table. D) organies elements into segments. Answer: A Diff: 1 age !ef: "12 AA$S%: &se of '( $ASE: $ontent b*ecti+e: .01) (he pro*ect operation A) combines relational tables to pro+ide the user with more information than is otherwise a+ailable. %) creates a subset consisting of columns in a table. $) organies elements into segments. D) identifies the table from which the columns will be selected. Answer: % Diff: 1 age !ef: "12 AA$S%: &se of '( $ASE: $ontent b*ecti+e: .0") Cou are creating a +ideo and animation sharing 9eb site whose content will be supplied b/ content, +ideo, and applets stored in a database and /ou anticipate +er/ high loads on the ser+er. 9hich of the following D%Ss will most li3el/ ser+e /our needs= A) ob*ect8relational D%S %) relational D%S $) hierarchical D%S D) D%S Answer: A Diff: " age !ef: "12 AA$S%: &se of '( $ASE: Anal/sis b*ecti+e: .0-) (he t/pe of database management approach that can handle multimedia is the A) hierarchical D%S. %) relational D%S. $) networ3 D%S. D) ob*ect8oriented D%S. Answer: D Diff: 1 age !ef: "12 AA$S%: &se of '( $ASE: $ontent b*ecti+e: .6 Copyright © 2012 Pearson Education, Inc.
00) (he data dictionar/ ser+es as an important data management tool b/ A) assigning attributes to the data. %) creating an in+entor/ of the data elements contained in the database. $) presenting data as end users or business specialists would percei+e them. D) maintaining data in updated form. Answer: % Diff: " age !ef: "14 AA$S%: &se of '( $ASE: $ontent b*ecti+e: ." 02) An automated or manual file that stores information about data elements and data characteristics such as usage, ph/sical representation, ownership, authoriation, and securit/ is the A) data dictionar/. %) data definition diagram. $) entit/8relationship diagram. D) relationship dictionar/. Answer: A Diff: " age !ef: "14 AA$S%: &se of '( $ASE: $ontent b*ecti+e: ." 0) (he specialied language programmers use to add and change data in the database is called A) a data access language. %) a data manipulation language. $) Structured Buer/ Language. D) a data definition language. Answer: % Diff: 1 age !ef: "14 AA$S%: &se of '( $ASE: $ontent b*ecti+e: ." 04) (he most prominent data manipulation language toda/ is A) Access. %) D%". $) SBL. D) $r/stal !eports. Answer: $ Diff: " age !ef: "14 AA$S%: &se of '( $ASE: $ontent b*ecti+e: ."
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05) D%Ss t/picall/ include report8generating tools in order to A) retrie+e and displa/ data. %) displa/ data in an easier8to8read format. $) displa/ data in graphs. D) perform predicti+e anal/sis. Answer: % Diff: " age !ef: "16 AA$S%: &se of '( $ASE: $ontent b*ecti+e: .1 06) (he process of streamlining data to minimie redun danc/ and aw3ward man/8to8man/ relationships is called A) normaliation. %) data scrubbing. $) data cleansing. D) data defining. Answer: A Diff: 1 age !ef: ""# AA$S%: &se of '( $ASE: $ontent b*ecti+e: .2#) A schematic of the entire database that describes the relationships in a database is called a?n) A) data dictionar/. %) intersection relationship diagram. $) entit/8relationship diagram. D) data definition diagram. Answer: $ Diff: " age !ef: ""1 AA$S%: &se of '( $ASE: $ontent b*ecti+e: .21) A one8to8one relationship between two en tities is s/mbolied in a diagram b/ a line that ends with A) two short mar3s. %) one short mar3. $) a crow;s foot. D) a crow;s foot topped b/ a short mar3. Answer: A Diff: age !ef: ""1 AA$S%: &se of '( $ASE: $ontent b*ecti+e: .-
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2") 9hich of the following is not one of the techniues used in 9eb mining= A) content mining %) structure mining $) usage mining D) user mining Answer: D Diff: " age !ef: ""5 AA$S%: !eflecti+e (hin3ing $ASE: $ontent b*ecti+e: .0 2-) Cou wor3 for a retail clothing chain whose primar/ outlets are in shopping malls and are conducting an anal/sis of /our customers and their preferences. Cou wish to find ou t if there are an/ particular acti+ities that /our customers engage in, or the t/pes of purchases made in the month before or after purchasing select items from /our store. (o do this, /ou will want to use data mining software that is capable of A) identif/ing associations. %) identif/ing clusters. $) identif/ing seuences. D) classification. Answer: $ Diff: " age !ef: ""2 AA$S%: Anal/tic S3ills $ASE: S/nthesis b*ecti+e: .0 20) Cou wor3 for an national car rental agenc/ and want to determine what characteristics are shared among /our most lo/al customers. (o do this, /ou will want to use data mining software that is capable of A) identif/ing associations. %) identif/ing clusters. $) identif/ing seuences. D) classification. Answer: D Diff: age !ef: ""2 AA$S%: Anal/tic S3ills $ASE: S/nthesis b*ecti+e: .0
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22) A data warehouse is composed of A) historical data from legac/ s/stems. %) current data. $) internal and e7ternal data sources. D) historic and current internal data. Answer: D Diff: " age !ef: """ AA$S%: &se of '( $ASE: $ontent b*ecti+e: .0 2) A data mart usuall/ can be constructed more rapidl/ and at lower cost than a data warehouse because A) a data mart t/picall/ focuses on a single sub*ect area or line of business. %) all the information is historical. $) a data mart uses a 9eb interface. D) all of the information belongs to a single compan/. Answer: A Diff: 1 age !ef: ""AA$S%: &se of '( $ASE: $ontent b*ecti+e: .0 24) (ools for anal/ing data to help users find patterns, relationships, and insights and ma3e better business decisions are 3nown as A) DSS. %) business intelligence. $) LA. D) data mining. Answer: % Diff: " age !ef: ""0 AA$S%: &se of '( $ASE: $ontent b*ecti+e: .0 25) (he tool that enables users to +iew the same data in different wa/s using multiple dimensions is A) predicti+e anal/sis. %) SBL. $) LA. D) data mining. Answer: $ Diff: age !ef: ""0 AA$S%: &se of '( $ASE: $ontent b*ecti+e: .0
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26) LA is a tool for enabling A) users to obtain online answers to ad8hoc uestions in a rapid amount of time. %) users to +iew both logical and ph/sical +iews of data. $) programmers to uic3l/ diagram data relationships. D) programmers to normalie data. Answer: A Diff: 1 age !ef: ""0 AA$S%: &se of '( $ASE: $ontent b*ecti+e: .0 #) Data mining is a tool for allowing users to A) uic3l/ compare transaction data gathered o+er man/ /ears. %) find hidden relationships in data. $) obtain online answers to ad hoc uestions in a rapid amount of time. D) summarie massi+e amounts of data into much smaller, traditional reports. Answer: % Diff: " age !ef: ""08""2 AA$S%: &se of '( $ASE: $ontent b*ecti+e: .0 1) 'n terms of data relationships, associations refers to A) e+ents lin3ed o+er time. %) patterns that describe a group to which an item belongs. $) occurrences lin3ed to a single e+ent. D) undisco+ered groupings. Answer: $ Diff: age !ef: ""2 AA$S%: &se of '( $ASE: $ontent b*ecti+e: .0 ") !!!!!!!! tools are used to anal/e large unstructured data sets, such as e8mail, memos, sur+e/ responses, etc., to disco+er patterns and relationships. A) LA %) (e7t mining $) 9eb mining D) 9eb content mining Answer: % Diff: " age !ef: "" AA$S%: &se of '( $ASE: $ontent b*ecti+e: .0
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-) An alternati+e to using application ser+er software for interfacing between a 9eb ser+er and bac38end databases is A) $<'. %) >(L. $) a+a. D) SBL. Answer: A Diff: 1 age !ef: ""6 AA$S%: &se of '( $ASE: $ontent b*ecti+e: .0 0) (he organiation;s rules for sharing, disseminating, acuiring, standardiing, classif/ing, and in+entor/ing information is called a?n) A) information polic/. %) data definition file. $) data ualit/ audit. D) data go+ernance polic/. Answer: A Diff: " age !ef: "-# AA$S%: &se of '( $ASE: $ontent b*ecti+e: .2 2) (he special organiational function whose responsibilities include the technical and operational aspects of managing data, including ph/sical database design and maintenance, is called A) data administration. %) database administration. $) information polic/ administration. D) data auditing. Answer: % Diff: 1 age !ef: "-# AA$S%: &se of '( $ASE: $ontent b*ecti+e: .2
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) 9hich common database challenge is illustrated b/ a person recei+ing multiple copies of an L.L. %ean catalog, each addressed to a slightl/ different +ariation of his or her full na me= A) data normaliation %) data accurac/ $) data redundanc/ D) data inconsistenc/ Answer: D Diff: age !ef: "-1 AA$S%: &se of '( $ASE: Anal/sis b*ecti+e: .2 4) Detecting and correcting data in a database or file that are incorrect, incomplete, improperl/ formatted, or redundant is called A) data auditing. %) defragmentation. $) data scrubbing. D) data optimiation. Answer: $ Diff: 1 age !ef: "-1 AA$S%: &se of '( $ASE: $ontent b*ecti+e: .2 5) Cou are creating a database to store temperature and wind data from national airport locations. 9hich of the following fields is the most li3el/ candidate to use as the basis for a primar/ 3e/ in the Airport table= A) address %) cit/ $) airport code D) state Answer: $ Diff: " age !ef: "10 AA$S%: Anal/tic S3ills $ASE: Anal/sis b*ecti+e: .6) Data cleansing not onl/ corrects errors but also A) establishes logical relationships between data. %) structures data. $) normalies data. D) enforces consistenc/ among different sets of data. Answer: D Diff: " age !ef: "-1 AA$S%: &se of '( $ASE: $ontent b*ecti+e: .2 1 Copyright © 2012 Pearson Education, Inc.
4#) 9hich of the following is ( a method for performing a data ualit/ audit= A) sur+e/ing entire data files %) sur+e/ing samples from data files $) sur+e/ing data definition and uer/ files D) sur+e/ing end users about their perceptions of data ualit/ Answer: $ Diff: age !ef: "-1 AA$S%: Anal/tic S3ills $ASE: Anal/sis b*ecti+e: .2 41) Databases record information about general categories of information referred to as @@@@@@@@. Answer: entities Diff: 1 age !ef: "1# AA$S%: &se of '( $ASE: $ontent b*ecti+e: .1 4") Data @@@@@@@@ describes a situation in which the same attribute of a data entit/ ma/ ha+e different +alues. Answer: inconsistenc/ Diff: " age !ef: "11 AA$S%: &se of '( $ASE: $ontent b*ecti+e: .1 4-) A?n) @@@@@@@@ +iew shows data as it is actuall/ organied and structured on the data storage media. Answer: ph/sical Diff: 1 age !ef: "1" AA$S%: &se of '( $ASE: $ontent b*ecti+e: .1 40) D%S ha+e a?n) @@@@@@@@ capabilit/ to specif/ the structure of the content of the database. Answer: data definition Diff: " age !ef: "14 AA$S%: &se of '( $ASE: $ontent b*ecti+e: ."
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42) !elational D%Ss use @@@@@@@@ rules to ensure that relationships between coupled tables remain consistent. Answer: referential integrit/ Diff: age !ef: ""# AA$S%: &se of '( $ASE: $ontent b*ecti+e: ." 4) 'n a clientser+er en+ironment, a D%S is located on a dedicated computer called a?n) @@@@@@@@. Answer: database ser+er Diff: " age !ef: ""1 AA$S%: &se of '( $ASE: $ontent b*ecti+e: .44) 'n @@@@@@@@, a data mining tool disco+ers different groupings within data, such as finding affinit/ groups for ban3 cards. Answer: clustering Diff: " age !ef: ""2 AA$S%: &se of '( $ASE: $ontent b*ecti+e: .0 45) (he techniue of using data mining, historical data, and assumptions about future conditions is called @@@@@@@@. Answer: predicti+e anal/tics Diff: " age !ef: "" AA$S%: !eflecti+e (hin3ing $ASE: $ontent b*ecti+e: .0 46) A?n) @@@@@@@@ is software that handles all application operations between browser8based computers and a compan/;s bac38end business applications or databases. Answer: application ser+er Diff: 1 age !ef: ""6 AA$S%: &se of '( $ASE: $ontent b*ecti+e: .0
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5#) 'n data mining, the techniue of @@@@@@@@ uses a series of e7isting +alues to predict what other +alues will be. Answer: forecasting Diff: " age !ef: ""2 AA$S%: &se of '( $ASE: $ontent b*ecti+e: .0 51) (he small publishing compan/ /ou wor3 for wants to create a new database for storing information about all of their author contracts. 9hat factors will influence ho w /ou design the database= Answer: Student answers will +ar/, but should include some assessment of data ualit/G business processes and user needsG and relationship to e7isting '( s/stems. He/ points to include are: Data accurac/ when the new data is input, establishing a good data model, determining which data is important and anticipating what the possible uses for the data will be, be/ond loo3ing up contract information, technical difficulties lin3ing this s/stem to e7isting s/stems, new business processes for data input and handling, and contracts management, determining how end users will use the data, ma3ing data definitions consistent with other databases, what methods to use to cleanse the data. Diff: " age !ef: "1#8"1", "-#8"-1 AA$S%: Anal/tic S3ills $ASE: S/nthesis b*ecti+e: .2 5") 9hen /ou design the new contracts database for the publishing house mentioned abo+e, what fields do /ou anticipate needing= 9hich of these fields might be in use in other databases used b/ the compan/= Answer: Author first name, author last name, author address, agent name and address, title of boo3, boo3 'S%, date of contract, amount of mone/, pa/ment schedule, date contract ends. ther databases might be an author database ?author names, address, and agent details), a boo3 title database ?title and 'S% of boo3), and financial database ?pa/ments made). Diff: " age !ef: "#68"12 AA$S%: Anal/tic S3ills $ASE: S/nthesis b*ecti+e: .1
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5-) List at least three conditions that contribute to d ata redundanc/ and inconsistenc/. Answer: Data redundanc/ occurs when different di+isions, functional areas, and groups in an organiation independentl/ collect the same piece of information. %ecause it is collected and maintained in so man/ different places, the same data item ma/ ha+e: ?1) different meanings in different parts of the organiation, ?") different names ma/ be used for the same item, and ?-) different descriptions for the same condition. 'n addition, the fields into which the data is gathered ma/ ha+e different field names, different attributes, or different constraints. Diff: " age !ef: "11 AA$S%: Anal/tic S3ills $ASE: Anal/sis b*ecti+e: .1 50) List and describe three main capabilities or tools of a D%S. Answer: A data definition capabilit/ to specif/ the structure of the content of the database. (his capabilit/ would be used to create database tables and to define the characteristics of the fields in each table. A data dictionar/ to store definitions of data elements in the database and their characteristics. 'n large corporate databases, the data dictionar/ ma/ capture additional information, such as usageG ownershipG authoriationG securit/G and the indi+iduals, business functions, programs, and reports that use each data element. A data manipulation language, such as SBL, that is used to add, change, delete, and retrie+e the data in the database. (his language contains commands that permit end users and programming specialists to e7tract data from the database to satisf/ information reuests and de+elop applications. Diff: " age !ef: "148"15 AA$S%: Anal/tic S3ills $ASE: Anal/sis b*ecti+e: ." 52) 9hat t/pes of relationships are possible in a relational d atabase= Describe and gi+e an e7ample of each. Answer: A one8to8one relationship occurs when each record in one table has onl/ one related record in a second table. An e7ample might be a table of salespeople and a separate table of compan/ cars. Each salesperson can onl/ ha+e one car, or be related to the one car in the database. A one8to8man/ relationship occurs when a record in one table has man/ related records in a second table. An e7ample might be a table of salespeople and clients. Each salesperson ma/ ha+e se+eral clients. A man/8to8man/ relationship occurs when records in one table ha+e man/ related records in a second table, and the records in the second table ha+e man/ related records in the first table. An e7ample might be a clients table and a products table. $lients ma/ bu/ more than one product, and products are sold to more than one client. Diff: age !ef: ""1 AA$S%: &se of '( $ASE: S/nthesis b*ecti+e: ."
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5) 'dentif/ and describe three basic operations used to e7tract useful sets of data from a relational database. Answer: (he select operation creates a subset consisting of all records ?rows) in the table that meets stated criteria. (he *oin operation combines relational tables to pro+ide the user with more information than is a+ailable in indi+idual tables. (he pro*ect operation creates a subset consisting of columns in a table, permitting the user to create new tables that contain onl/ the information reuired. Diff: " age !ef: "12 AA$S%: &se of '( $ASE: Anal/sis b*ecti+e: ." 54) Describe the wa/s in which database technologies could be used b/ an office stationer/ suppl/ compan/ to achie+e low8cost leadership. Answer: Sales databases could be used to ma3e the suppl/ chain more efficient and minimie warehousing and transportation costs. Cou can also use sales databases to determine what supplies are in demand b/ which customers, and whether needs are different in different geographical areas. DSS databases using business intelligence could be used to predict future trends in office suppl/ needs, to help anticipate demand, and to determine the most efficient methods of transportation and deli+er/. Diff: age !ef: "1-, ""18"-# AA$S%: &se of '( $ASE: E+aluation b*ecti+e: .0 55) Describe the wa/s in which database technologies could be used b/ an office stationer/ suppl/ compan/ to achie+e product differentiation. Answer: roduct databases could be made a+ailable to customers for greater con+enience when ordering online. Databases could be used to trac3 customer preferences and to help anticipate customer desires. Sales databases could also help a client anticipate when the/ would need to re8 suppl/, pro+iding an additional ser+ice. Data mining could help anticipate trends in sales or other factors to help determine new ser+ices and products to sell to the clients. Diff: age !ef: ""18"-# AA$S%: &se of '( $ASE: E+aluation b*ecti+e: .0
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56) 9hat ma3es data mining an important business tool= 9hat t/pes of information does data mining produce= 'n what t/pe of circumstance would /ou ad+ise a compan/ to use data mining= Answer: Data mining is one of the data anal/sis tools that helps users ma3e better business decisions and is one of the 3e/ tools of business intelligence. Data mining allows users to anal/e large amounts of data and find hidden relationships between data that otherwise would not be disco+ered. For e7ample, data mining might find that a customer that bu/s product is ten times more li3el/ to bu/ product C than other customers. Data mining finds information such as: I Associations or occurrences that are lin3ed to a single e+ent. I Seuences, e+ents that are lin3ed o+er time. I $lassification, patterns that describe the group to which an item belongs, found b/ e7amining e7isting items that ha+e been classified and b/ inferring a set of rules. I $lusters, unclassified but related groups. ' would ad+ise a compan/ to use data mining when the/ are loo3ing for new products and ser+ices, or when the/ are loo3ing for new mar3eting techniues or new mar3ets. Data mining might also be helpful when tr/ing to anal/e unanticipated problems with sales whose causes are difficult to identif/. Diff: age !ef: ""08"" AA$S%: &se of '( $ASE: E+aluation b*ecti+e: .0 6#) 9hat are the differences between data mining and LA= 9hen would /ou ad+ise a compan/ to use LA= Answer: Data mining unco+ers hidden relationships and is used when /ou are tr/ing to disco+er data and new relationships. 't is used to answer uestions such as: Are there an/ product sales that are related in time to other product sales= 'n contrast, LA is used to anal/e multiple dimensions of data and is used to find answers to comple7, but 3nown, uestions, such as: 9hat were sales of a product bro3en down b/ month and geographical region, and how did those sales compare to sales forecasts= Diff: " age !ef: ""08"" AA$S%: &se of '( $ASE: E+aluation b*ecti+e: .0
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