The Data Warehouse Chapter 11 The Data Warehouse Database Systems Design Implementation

							        Chapter 11
The Data Warehouse

Database Systems:
Design, Implementation, and
Management, Seventh Edition, Rob
and Coronel                        1
Multidimensional Data Analysis
Techniques (continued)




                                 2   2
Multidimensional Data Analysis
Techniques (continued)




                             3   3
Advanced Database Support
 Advanced data access features include:
    Access to many different kinds of DBMSs, flat
   files, and internal and external data sources
    Access to aggregated data warehouse data as
   well as to detail data found in operational
   databases
    Advanced data navigation
   Rapid and consistent query response times
   Ability to map end-user requests to appropriate
   data source and then to proper data access
   language (usually SQL)
                                                     4   4
    Support for very large databases
Easy-to-Use End-User Interface
  Many of interface features are
  “borrowed” from previous generations of
  data analysis tools that are already
  familiar to end users
    Makes OLAP easily accepted and readily
    used



                                             5   5
Client/Server Architecture
  Provides framework within which new
  systems can be designed, developed,
  and implemented
    Enables OLAP system to be divided into
    several components that define its
    architecture
    OLAP is designed to meet ease-of-use as
    well as system flexibility requirements


                                              6   6
OLAP Architecture




                    7   7
OLAP Architecture (continued)




                                8   8
OLAP Architecture (continued)
 Designed to use both operational and data
 warehouse data
 Defined as an “advanced data analysis
 environment that supports decision
 making, business modeling, and an
 operation’s research activities”
 In most implementations, data warehouse
 and OLAP are interrelated and
 complementary environments
                                        9   9
OLAP Architecture (continued)




                            10 10
OLAP Architecture (continued)




                            11 11
Relational OLAP
 Provides OLAP functionality by using
 relational databases and familiar relational
 query tools to store and analyze
 multidimensional data
 Adds following extensions to traditional
 RDBMS:
   Multidimensional data schema support within
   RDBMS
   Data access language and query performance
   optimized for multidimensional data         12 12
Relational OLAP




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