LEADER 05678nam 22008413u 450 001 9910964981303321 005 20210114043336.0 010 $a9781849689816 010 $a1849689814 035 $a(CKB)2550000001179132 035 $a(EBL)1581056 035 $a(SSID)ssj0001174058 035 $a(PQKBManifestationID)11673439 035 $a(PQKBTitleCode)TC0001174058 035 $a(PQKBWorkID)11107328 035 $a(PQKB)10973893 035 $a(PPN)228033411 035 $a(OCoLC)870467562 035 $a(OCoLC)ocn870467562 035 $a(FR-PaCSA)88849797 035 $a(CaSebORM)9781849689809 035 $a(MiAaPQ)EBC1581056 035 $a(FRCYB88849797)88849797 035 $a(DE-B1597)722658 035 $a(DE-B1597)9781849689816 035 $a(EXLCZ)992550000001179132 100 $a20140106d2013|||| u|| | 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aSQL Server Analysis Services 2012 Cube Development Cookbook 205 $a1st edition 210 $aBirmingham $cPackt Publishing$d2013 215 $a1 online resource (340 p.) 225 1 $aQuick answers to common problems 300 $aDescription based upon print version of record. 311 08$a9781849689809 311 08$a1849689806 311 08$a9781306280204 311 08$a1306280206 327 $aCover; Copyright; Credits; About the Authors; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Introduction to Multidimensional Data Model Design; Introduction; The business value of Business Intelligence; Challenges and barriers of effective BI; Overcoming BI challenges and barriers; Choosing multidimensional or Tabular models; Star- or Snowflake-relational schema; A sample scenario for choosing the Snowflake schema; Chapter 2: Defining Analysis Services Dimensions; Introduction; Defining data sources; Defining data source views 327 $aDefining entity relationships in DSVExtending data source views; Creating named calculations and queries; Creating simple dimensions; Building dimension hierarchies; Setting essential attribute properties; Browsing dimension data; Sorting the attributes; Customizing advanced attribute properties; Creating parent-child dimensions; Creating the date and time dimensions; Chapter 3: Creating Analysis Services Cubes; Introduction; Defining measure groups and measures; Setting measure properties; Browsing the cube data; Dimension usage with measure group; Examining cube file structures 327 $aPartitioning strategiesDefining partition slice; Merging partitions; Defining aggregation designs; Distinct count measure groups; Enabling write-back feature; Deployment options; Chapter 4: Extending and Customizing Cubes; Introduction; Defining calculated measures; Defining named sets; Defining drillthrough actions; Defining URL actions; Defining reporting actions; Defining key performance indicators; Defining perspectives; Defining translations; Defining measure expressions; Chapter 5: Optimizing Dimension and Cube Processing; Introduction; Understanding dimension processing options 327 $aLearning about basic dimension processingLearning advanced dimension processing options; Using out-of-line bindings for dimension processing; Dealing with partition processing options; Using SQL Server Integration Services to process Analysis Services objects; Monitoring and tuning processing performance; Chapter 6: MDX; Introduction; Returning data on the query axes; Limiting the query output; Sorting the query output; Defining query level calculations and named sets; Navigating dimension hierarchies; Working with the Time dimensions; MDX script's functionality 327 $aMonitoring and tuning MDX queriesChapter 7: Analysis Services Security; Introduction; Managing instance-level administrative security; Managing database-level security; Managing cube-level security; Managing dimension hierarchy-level security; Implementing dynamic dimension security; Implementing cell-level security; Chapter 8: Administering and Monitoring Analysis Services; Introduction; SSAS instance configuration options; Creating and dropping databases; Monitoring SSAS instance using Activity Viewer; Monitoring SSAS instance using DMVs; Cancelling a session 327 $aChecking whether cubes are accessible 330 $aA practical cookbook packed with recipes to help developers produce data cubes as quickly as possible by following step by step instructions, rather than explaining data mining concepts with SSAS.If you are a BI or ETL developer using SQL Server Analysis services to build OLAP cubes, this book is ideal for you. Prior knowledge of relational databases and experience with Excel as well as SQL development is required. 606 $aClient/server computing 606 $aComputer networks -- Security measures 606 $aSQL server 606 $aWeb servers 606 $aEngineering & Applied Sciences$2HILCC 606 $aComputer Science$2HILCC 615 4$aClient/server computing. 615 4$aComputer networks -- Security measures. 615 4$aSQL server. 615 4$aWeb servers. 615 7$aEngineering & Applied Sciences 615 7$aComputer Science 676 $a005.75 676 $a005.7585 700 $aDewald$b Baya$01798697 701 $aTurley$b Paul$0850105 701 $aHughes$b Steve$0611924 801 0$bAU-PeEL 801 1$bAU-PeEL 801 2$bAU-PeEL 906 $aBOOK 912 $a9910964981303321 996 $aSQL Server Analysis Services 2012 Cube Development Cookbook$94341597 997 $aUNINA