DW Lecture II (2)

DW Lecture II (2) - Data ware housing and Busine I nte...

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By Dr. Atanu Rakshit Data warehousing and Business Intelligence using SAS (Lecture II)
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II. On-Line Analytical Processing (OLAP) Making Decision Support Possible
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3 Typical OLAP Queries Write a multi-table join to compare sales for each  product line YTD this year vs. last year.  Repeat the above process to find the top 5 product  contributors to margin.  Repeat the above process to find the sales of a product  line to new vs. existing customers.  Repeat the above process to find the customers that  have had negative sales growth. 
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4 * Reference: http://www.arborsoft.com/essbase/wht_ppr/coddTOC.html http://www.arborsoft.com/essbase/wht_ppr/coddTOC.html What Is OLAP? Online Analytical Processing - coined by  EF Codd in 1994 paper contracted by  Arbor Software * Generally synonymous with earlier terms such as  Decisions Support, Business Intelligence, Executive  Information System OLAP = Multidimensional Database MOLAP:  Multidimensional OLAP (Arbor Essbase, Oracle  Express) ROLAP:  Relational OLAP (Informix MetaCube,  Microstrategy DSS Agent)
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5 The OLAP Market Rapid growth in the enterprise market 1995:  $700 Million 1997:  $2.1 Billion Significant consolidation activity among major  DBMS vendors 10/94:  Sybase acquires ExpressWay 7/95:  Oracle acquires Express  11/95:  Informix acquires Metacube 1/97:  Arbor partners up with IBM 10/96:  Microsoft acquires Panorama Result:  OLAP shifted from small vertical niche  to mainstream DBMS category
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6 Conceptual Model for OLAP Numeric measures to be analyzed e.g.  Sales (Rs), sales (volume), budget,  revenue, inventory Dimensions other attributes of data, define the space e.g., store, product, date-of-sale hierarchies  on dimensions  e.g. branch -> city -> state
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7 Strengths of OLAP It is a powerful visualization paradigm It provides fast, interactive response times It is good for analyzing time series It can be useful to find some clusters and  outliers Many vendors offer OLAP tools
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8 OLAP Is FASMI Fast Analysis Shared Multidimensional Information
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9 OLAP Is FASMI Fast System is targeted to deliver most  response to user within specified time  frame Analysis The system can cope with any  business logic and statistical analysis  that is relevant for the application and  the user
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10 OLAP Is FASMI Shared The system implements all the  security requirements for  confidentiality (possible down to cell  level) and, if multiple write access is  needed, concurrent update locking at  appropriate level
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11 OLAP Is FASMI Multidimensional The system must provide a  multidimensional conceptual view of 
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