IBM WebSphere Information Analyzer and Data Quality Assessment

538 IBM WebSphere Information Analyzer and Data Quality Assessment

inline validation and transformation of complex data types such as the U.S.

Health Insurance Portability and Accountability Act (HIPAA), along with

high-speed joins and sorts of heterogeneous data. IBM Information Server

also provides high-volume, complex data transformation and movement

functionality that can be used for stand-alone extract/transform/load (ETL)

scenarios or as a real-time data processing engine for applications or

processes.

The WebSphere DataStage product modules currently provide this

functionality.

򐂰 Deliver your information

IBM Information Server provides the ability to virtualize, synchronize, or move

information to the people, processes, or applications that need it. Information

can be delivered through federation or time-based or event-based

processing, moved in large bulk volumes from location to location, or

accessed in place when it cannot be consolidated. IBM Information Server

provides direct, native access to a wide variety of information sources, both

mainframe and distributed. It provides access to databases, files, services,

and packaged applications and to content repositories and collaboration

systems. Companion products allow high-speed replication, synchronization,

and distribution across databases, change data capture, and event-based

publishing of information.

The WebSphere Federation Server product module currently provides this

functionality.

A.2.4 Unified parallel processing

Much of the work that IBM Information Server does takes place within the parallel

processing engine. The engine handles data processing needs as diverse as

performing analysis of large databases for WebSphere Information Analyzer,

data cleansing for WebSphere QualityStage, and complex transformations for

WebSphere DataStage. This parallel processing engine is designed to deliver:

򐂰 Parallelism and pipelining to complete increasing volumes of work in

decreasing time windows.

– Data partitioning is an approach to parallelism that involves breaking the

record set into partitions, or subsets of records. Data partitioning generally

provides linear increases in application performance.

IBM Information Server partitions data automatically based on the type of

partition that the stage requires. In a well-designed, scalable architecture,

the developer does not need to be concerned about the number of

partitions that will run, the ability to increase the number of partitions, or

re-partitioning data.