cs2032 data warehousing and data mining

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CS2032 DATA WAREHOUSING AND DATA MINING. UNIT II BUSINESS ANALYSIS. Contents. Reporting and Query tools and Applications Tool Categories The Need for Applications Cognos Impromptu Online Analytical Processing (OLAP) Need –Multidimensional Data Model OLAP Guidelines - PowerPoint PPT Presentation

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CS2032 DATA WAREHOUSING AND DATA MINING

UNIT II BUSINESS ANALYSISCS2032 DATA WAREHOUSING AND DATA MININGContentsReporting and Query tools and ApplicationsTool CategoriesThe Need for ApplicationsCognos ImpromptuOnline Analytical Processing (OLAP)Need Multidimensional Data ModelOLAP Guidelines Multidimensional versus Multirelational OLAPCategories of ToolsOLAP Tools and the InternetReporting and Query Tools and ApplicationsTool CategoriesReporting ToolsManaged Query ToolsExecutive Information System ToolsOLAP ToolsData Mining ToolsThe Need for ApplicationsCognos ImpromtuApplicationsPowerBuilderForteInformation BuilderReporting ToolsProduction Reporting ToolsLet companies generate regular operational reportsSupport high volume batch jobsCalculating and Printing Paychecks(3GL)COBOL, Information Builders, Inc.s Focus(4GL)MITIs SQR(High-end Client/Server Tools)Desktop Report WritersLet users design and run reportsGraphical Interfaces and Built-in charting functionsCrystal Reports, Actuate Reporting System, IQ objectsManaged Query ToolsShield end users from the complexities of SQL and database structuresMeta layerSupport asynchronous query executionIntegrate with web serversEmbed OLAP and Data Mining Features

Executive Information System ToolsPredate report writers and managed query toolsFirst deployed on MainframesAllow to build customized, graphical decision support applicationsGives managers and executives a high level view of business and access to external sourcesEg: Pilot Software, Forest and Trees, Comshare, Oracles Express AnalyzerOLAP ToolsProvide and intuitive way to view corporate dataAggregate data along common business objectsUsers can drill down, across, or up levels in each dimensionData Mining ToolsUser variety of statistical and artificial-intelligence algorithmsAnalyze the correlation of variables in the data and ferret out interesting patterns and relationships to investigateExampleIBMs Intelligent MinerDataMindPilots Discovery ServerOffers simple UIs plug in directly to existing OLAPThe Need for ApplicationsAccess Types to the dataSimple tabular from reportingAd hoc user-specified queriesPredefined repeatable queriesComplex queriesRankingMultivariable analysisTime series analysisData visualization, graphing, charting, and pivotingComplex textual searchStatistical analysisCognos ImpromptuOverviewThe impromptu Information CatalogObject-oriented architectureReportingImpromptu Request ServerSupported Databases

Cognos Impromtu: OverviewEnterprise solution for interactive database reportingObject oriented architectureEnsures control and administrative consistency across all users and reportsGUIDatabase reporting toolSupports single user reporting / multi users reportingCognos Impromtu: Information CatalogLAN based repository of business knowledge and data access rulesInsulates users from db technical aspectsProtects databasePresents the database in a easy wayAdministrators are free to organize database itemsCognos Impromtu: OO ArchitectureDrives inheritance based administration and distributed catalogsGovernorsActivities of GovernorsQuery activityProcessing locationDatabase connectionsReporting permissionsUser profilesClient/Server BalancingDatabase TransactionsSecurity by valueFiled and table securityCognos Impromtu: ReportingPicklists and promptsCustom templatesException reportingConditional filtersConditional highlightingConditional displayInteractive reportingFramesList frameForm frameCross-tab frameChart frameText FramePicture FrameOLE FrameCognos Impromtu: Request ServerAllows client to off-load the query process to the server Scheduling regular and recurring standard reportsReducing network traffic Runs on HP/UX 9.X, IBM AIX 4.X, Sun Solaris 2.4Support data maintain in ORACLE 7.x and SYBASE System 10/11On-Line Analytical Processing(OLAP)(1)Need for OLAPMultidimensional Data ModelOLAP GuidelinesMultidimensional versus Multirelational OLAPCategorization of OLAP ToolsMOLAPROLAPManaged Query Environment(MQE)On-Line Analytical Processing(OLAP)(2)State of the MarketCognos PowerPlayIBI FOCUS FusionPilot SoftwareOLAP Tools and the InternetOLAP

OLAP

Multidimensional Data ModelViewing data as in a cube

OLAP GuidelinesMultidimensional conceptual viewTransparencyAccessibilityConsistent reporting performanceClient/server architectureGeneric dimensionalityDynamic sparse matrix handlingMultiuser supportUnrestricted cross-dimensional operations

Categorization of OLAP ToolsMOLAPROLAPMOLAP

ROLAP

State of the MarketCognos PowerPlayIBI FOCUS FusionPilot SoftwareOLAP Tools and the Internet

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