WebSphere® DataStage™ has
the functionality, flexibility, and scalability that are required to meet
the most demanding data integration requirements.
WebSphere DataStage has
the following capabilities:
- Integrates data from the widest range of enterprise and external data
sources
- Incorporates data validation rules
- Processes and transforms large amounts of data by using scalable parallel
processing
- Handles very complex transformations
- Manages multiple integration processes
- Provides direct connectivity to enterprise applications as sources or
targets
- Leverages metadata for analysis and maintenance
- Operates in batch, real time, or as a Web service
Scenarios for data transformation
The following
scenarios show how organizations use WebSphere DataStage to address complex data transformation
and movement needs.
- Retail: Consolidating financial systems
- A leading retail chain watched sales flatten for the first time in years.
Without insight into store-level and unit-level sales data, they could not
adjust shipments or merchandising to improve results. With long production
lead-times and existing large volume manufacturing contracts, they could not
change their product lines quickly, even if they understood the problem. To
integrate the company’s forecasting, distribution, replenishment, and inventory
management processes, they needed a way to migrate financial reporting data
from many systems to a single system of record.
The company deployed IBM® Information
Server to deliver data integration services between business applications
in both messaging and batch file environment. WebSphere DataStage is now the common company-wide
standard for transforming and moving data. The service-oriented interface
allows them to define common integration tasks and reuse them throughout the
enterprise. New methodology and reusable components for other global projects
will lead to additional future savings in design, testing, deployment and
maintenance.
- Banking: Understanding the customer
- A large retail bank understood that the more it knew about its customers,
the better it could market its products, including credit cards, savings accounts,
checking accounts, certificates of deposit, and ATM services. Faced with terabytes
of customer data from vendor sources, the bank recognized the need to integrate
the data into a central repository where decision-makers could retrieve it
for market analysis and reporting. Without a solution, the bank risked flawed
marketing decisions and lost cross-selling opportunities.
The bank used WebSphere DataStage to
automatically extract and transform raw vendor data, such as credit card account
information, banking transaction details and Web site usage statistics, and
load it into its data warehouse. From there, the company can generate reports
that let them track the effectiveness of programs and analyze their marketing
efforts. WebSphere DataStage helps
the bank maintain, manage, and improve its information management with an
IT staff of three instead of six or seven, saving hundreds of thousands of
dollars in the first year alone, and enabling it to use the same capabilities
more rapidly on other data integration projects.
Where WebSphere DataStage fits in the overall business
context
WebSphere DataStage enables an integral part
of the information integration process: data transformation, as Figure 1 shows:
WebSphere DataStage is
often deployed to systems such as enterprise applications, data warehouses,
and data marts. WebSphere DataStage provides
this functionality with extensive capabilities:
- Enables the movement and transformation of data between operational, transactional,
and analytical targets
- Helps a company determine how best to integrate data, either in batch
or in real time, to meet its business requirements
- Saves time and improves consistency of design, development, and deployment
IBM Information Server, Version 8.1
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