Tools are available to help implement data warehouses and include tools for data transformation, movement, querying, reporting, and analysis. These tools may come from different vendors and use different approaches, so it is important to select tools that are compatible and can share metadata. Key tools include those for data aggregation, visualization, querying, application development, executive information systems, online analytical processing, and data mining.

1. Tools for Data Warehousing :
A numberof toolsavailable todayare specificiallydesignedtohelpinthe implementationof adata
warehouse.These toolsprovidesfacilitiesfordesigningthe transformationandcleanuprules,data
movement(from operatrional sourcesintothe warehouse),enduserquery,reportinganddataanalysis.
Some toolsare vendorbasedforseveral stagesorquite often- multiplevendorsourceswill be required
for differenttoolsindifferentstages.Eachtool takesaslightly differentapproachtodata warehousing
and oftenmaintainitsownversionof metadatarepository.DataWarehouse designershave tobe careful
not to sacrifice the overall designtofitaspecifictool.Atthe same time ,the designershave tomake
sure that all selectedtoolsare compatiblewiththe givendatawarehouse environmentandwitheach
other.Therefore,itisbettertogofor a verycomprehensive tool.Thismeansthatall selectedtoolscan
use a common metadatarepository.
Alternatively,the tools shouldbe able tosource the metadatafromthe warehouse datadictionary(ifitis
available) orfroma _____ tool usedto designthe database inthe data warehouse.Anotheroptionis
to use metadatagateways that translate one toolsmetadataintoanothertoolsformat(Kimball 1996).
If these requirementsare notsatisfied,the resultingwarehouse environmentmayrapidlybecome
unamanagable,since everymodificationtothe warehouse datamodel mayinvolvesame significantand
labour-intensive changes tothe meta-datadefinitionsforeverytool inthe environmen.These changes
wouldhave tobe verifiedforconsistencyabdintegrity(____).
Followingare the toolsprovidedforthe datawarehouse:
 Data Aggregation
 Data Visualization
 ReportingandQuery tools
 ApplicationDevelopmenttools
 Executive InformationSystem(EIS) tools
 Online Analytical Processing(OLAP) tools
 Data Miningtools
1.Data Aggregation:
One can store data basedon eachtransactionor one can store itbased on a summary.
Whendata is summarized,the querieswillmove ata muchfasterrate. However,some of the
informationmaybe lostduringa queryandthisinformationmaybe importantforsolvingcertain
problems.Hence dataaggregationisrequiredtosolve the same problem.
2.Data Visualization:
The toolsthat are usedfordata visualizationwill presentvisual modelsof dat.Thisdatacouldcome in
the form of intricate 3D images.The goal of datavisualizationistoallow the usertoview trendsina
methodwhichiseasiertounderstandthancomplicatedmodelsthatare basedof statistics.

2. 3.Reporting and Query Tools:
Reportingtoolsinclude productionreportingtoolsandreportwriters.Productionreportingtoolsare
usedto generate regularoperational reportsorsupporthigh-volume batchjobssuchas customerorders
and staff paycheques.Reportwriters,onthe otherhand,are inexpensive desktoptoolsdesignedfor
endusers.
Querytoolsforrelational datawarehousesare designedtoacceptSQLor generate SQLstatements to
_______data storedinthe warehouse.Thesetools_______________________. The metalayeristhe
software thatprovidessubject-orientedviewsof adatabase and supports“point-and-click”creationof
SQL.
Querytoolsare popularwithusersof businessapplicationssuchasdemographicanalysisandcustomer
mailinglists.
4.ApplicationDevelopmenttools:
The requirementsof the endusersmaybe such that the builtincapabilitiesof reportingandquery
toolsare inadequate eitherbecause the requiredanalysiscannotbe performedorbecause the user
interactionrequiresanunreasonablyhighlevel of expertise bythe user.Inthissituation,useraccessmay
require the developmentof inhouse applicationsusinggraphical dataaccesstoolsdesignedprimarily
for clientserverenvironments.
5.Executive InformationSystem(EIS) Tools:
EIS,more recentlyreferredtoas“everybody’sinformationsystem”,were originallydevelopedto
supporthighlevel strategicdecisionmaking.However,the focusof these systemswidenedtoinclude
supportfor all levelsof management.EIStoolswere originallyassociatedwithmainframesenabling
usersto buildcustomized,graphical decisionsupportapplicationstoprovideanoverviewof the
organization’sdataandaccessto external datasources.
6.OnlineAnalytical Processing(OLAP) Tools:
OLAPtoolsare basedon the conceptof multidimensional databasesandallow asophisticateduser
to analyze the datausingcomplex,multi dimensional views.Typical businessapplicationforthese tools
include assessingthe effectivenessof amarketingcampaign,productsalesforecastingandcapacity
plannings.Thesetoolsassume thatthe dataisorganizedina multi-dimnsionalmodel supportedbya
relational database designedtoenable multi-dimensionalqueries.
7.Data MiningTools:
Data miningisthe processof discoveringmeaningfulnew correlations,patternsandtrendbymining
large amountof data usingstatistical,mathematical andartificial intelligence(AI) technique.Datamining
has the potential tosupersedethe capabilitiesof OLAPtools,asthe majorattractionof data miningisits
ablotyto buildpredictive ratherthanretrospective models.