LEADER 05519nam 2200697Ia 450 001 9910458636803321 005 20200520144314.0 010 $a1-281-01197-5 010 $a9786611011970 010 $a0-08-049593-1 035 $a(CKB)1000000000364134 035 $a(EBL)297173 035 $a(OCoLC)469607592 035 $a(SSID)ssj0000185816 035 $a(PQKBManifestationID)11174677 035 $a(PQKBTitleCode)TC0000185816 035 $a(PQKBWorkID)10210014 035 $a(PQKB)10986391 035 $a(MiAaPQ)EBC297173 035 $a(CaSebORM)9780123695123 035 $a(Au-PeEL)EBL297173 035 $a(CaPaEBR)ebr10180368 035 $a(CaONFJC)MIL101197 035 $a(EXLCZ)991000000000364134 100 $a20061212d2006 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aJoe Celko's analytics and OLAP in SQL$b[electronic resource] /$fJoe Celko 205 $a1st edition 210 $aSan Francisco, Calif. $cMorgan Kaufmann$dc2006 215 $a1 online resource (205 p.) 225 1 $aThe Morgan Kaufmann series in data management systems 300 $aIncludes index. 311 $a0-12-369512-0 327 $aFront Cover; Joe Celko's Analytics and OLAP in SOL; Copyright Page; Contents; Introduction; Beyond Queries; Some of the Differences between OLAP and OLTP; Corrections and Additionsx; Chapter 1. Basic Reports and History; 1.1 Cases; 1.2 Control-Break Reports; 1.3 Cross-Tabulation Reports; 1.4 Presentation Graphics; 1.5 Local Databases; Chapter 2. Cross-Tabulations; 2.1 Crosstabs by Cross-Join; 2.2 Crosstabs by Outer Joins; 2.3 Crosstabs by Subquery; 2.4 Crosstabs by CASE Expression; 2.5 Crosstabs with Row and Column Summaries; Chapter 3. Dimension Tables; 3.1 Star and Snowflake Schemas 327 $a3.2 Kinds of Dimensions3.3 Calendars and Temporal Data; 3.4 Helper Tables; 3.5 Surrogate Keys; 3.6 Degenerate Dimensions; Chapter 4. Data Migration and Scrubbing; 4.1 Pumping Data; 4.2 Verification and Validation; 4.3 Extract, Transform, and Load (ETL); 4.4 Databases Also Evolved; 4.5 Data Warehouses; 4.6 Extract, Load, and then Transform (E-L-T); 4.7 Scrubbing Data with Non-First-Normal-Form (1NF) Tables; Chapter 5. MERGE Statement; 5.1 Simple MERGE Statement; 5.2 Merging without the MERGE Statement; 5.3 TRIGGERs and MERGE; 5.4 Self-Referencing MERGE; Chapter 6. OLAP Basics; 6.1 Cubes 327 $a6.2 Dr. Codd's OLAP Rules6.3 MOLAP; 6.4 ROLAP; 6.5 HOLAP; 6.6 OLAP Query Languages; Chapter 7. GROUPING Operators; 7.1 GROUP BY GROUPING SET; 7.2 ROLLUP; 7.3 CUBES; 7.4 Notes about Usage; Chapter 8. OLAP Operators in SQL; 8.1 OLAP Functionality; 8.2 NTILE(); 8.3 Nesting OLAP functions; 8.4 Sample Queries; Chapter 9. Sparseness in Cubes; 9.1 Hypercube; 9.2 Dimensional Hierarchies; 9.3 Drilling and Slicing; Chapter 10. Data Quality; 10.1 Checking Columns for Value Counts; 10.2 Finding Rules in a Schema; 10.3 Feedback for Data Quality; 10.4 Further Reading; Chapter 11. Correlation 327 $a11.1 Causes and Correlation11.2 Linear Correlation; 11.3 Nesting Functions; 11.4 Further Reading; Chapter 12. Data Distributions; 12.1 Flat Distribution; 12.2 Zipfian Distribution; 12.3 Gaussian, Normal, or Bell Curve; 12.4 Poisson Distribution; 12.5 Logistic or "S" Distribution; 12.6 Pareto Distribution; 12.7 Distribution Discovery; 12.8 References; Chapter 13. Market-Basket Analysis; 13.1 Simple Example of a Market Basket; 13.2 Relational Division; 13.3 Romney's Division; 13.4 How to Use Relational Divisions; Chapter 14. Decision, Classification, and Regression Trees; 14.1 Casual Caldistics 327 $a14.2 Decision and Correlation Trees14.3 Entropy; 14.4 Other Algorithms and Software; Chapter 15. Computer-Intensive Analysis; 15.1 Bootstraps; 15.2 Subgroups; 15.3 Bayesian Analysis; 15.4 Clustering; Chapter 16. Relationship Analytics; 16.1 Adjacency List Model for General Graphs; 16.2 Covering Paths Model for General Graphs; 16.3 Conclusion and Solution; 16.4 Further Reading; Chapter 17. Database Architectures; 17.1 Parallelism; 17.2 Hashing; 17.3 Bit Vector Indexes; 17.4 Streaming Databases; 17.5 Further Reading; Chapter 18. MDX from a SQL Viewpoint; 18.1 MDX SELECT Statement 327 $a18.2 Hierarchical Navigation 330 $aBefore SQL programmers could begin working with OLTP (On-Line Transaction Processing) systems, they had to unlearn procedural, record-oriented programming before moving on to SQL's declarative, set-oriented programming. This book covers the next step in your growth. OLAP (On-Line Analytical Processing), Data Warehousing and Analytics involve seeing data in the aggregate and over time, not as single transactions. Once more it is time to unlearn what you were previously taught. This book is not an in-depth look at particular subjects, but an overview of many subjects that will give the 410 0$aMorgan Kaufmann series in data management systems. 517 1 $aJoe Celko's Analytics & OLAP in SQL 517 3 $aAnalytics and OLAP in SQL 606 $aOLAP technology 606 $aSQL (Computer program language) 608 $aElectronic books. 615 0$aOLAP technology. 615 0$aSQL (Computer program language) 676 $a005.7585 700 $aCelko$b Joe$0627493 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910458636803321 996 $aJoe Celko's analytics and OLAP in SQL$91212754 997 $aUNINA