NonStop Systems Introduction

The Relational Database Management System
NonStop Systems Introduction—527825-001
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ORDM Approach
Because decision support applications often involve very complex queries against
large data warehouses, support for decision support also means supporting optimal
performance and database manageability.
Performance is crucial because of the size of the data warehouses and the
time-consuming nature of many decision support queries. SQL/MX is designed to
optimize performance for decision support applications. For example, parallel
processing is employed to maximize system efficiency.
Database manageability is also an issue because of the unwieldy size of a large data
warehouse and the challenge of making efficient use of it. Tools and database
features that enhance manageability are available.
ORDM Approach
In the ORDM approach to data mining, many of the data mining tasks are performed in
the database itself. The ORDM approach identifies fundamental data structures and
operations that are common across a wide range of knowledge discovery tasks, and
builds such structures and operations into the DBMS.
In the ORDM approach, tools and applications perform data-intensive data-preparation
tasks in the DBMS by using an SQL interface. This approach allows the powerful and
parallel DBMS data manipulation capabilities to be utilized for the demanding data
preparation stage of the knowledge discovery process.
Fundamental data structures and operations are built into the DBMS to support a wide
range of knowledge discovery tasks and algorithms in an efficient and scalable
manner.
The ORDM approach offers several advantages over the traditional approach. The
primary advantages of ORDM technology over traditional data mining techniques
include:
•
The ability to mine much larger data sets, not just data in flat-file extracts
•
Simplified data management
•
More complete results
•
Better performance and reduced cycle times
•
Extensibility to mine complex data types