Oracle Ships New Warehouse Builder Tool

Users can buy optional features to allow the software to work in heterogeneous environments.
Oracle this week shipped release two of its Oracle Warehouse Builder 10g database tool, which solution providers can use to cleanse data and build analytics applications.

Oracle Warehouse Builder 10g Release 2, a database design and Extraction, Transformation and Load (ETL) application, helps customers manage the life cycle of data and metadata. Oracle said it also plans to embed core ETL capabilities into the various versions of its database software.

Users of Oracle 10g Enterprise Edition Release 2, too, can purchase additional ETL capabilities via a Warehouse Builder Enterprise ETL option for heterogeneous environments, with support for user-defined objects and associations. In addition, a Data Quality option adds data profiling and rules, cleansing, auto-correction and auditing.

The ETL option costs $10,000 per CPU or $200 per user. The Data Quality option runs $15,000 per CPU or $300 per user. Connectors for PeopleSoft Enterprise, Oracle E-Business Suite and SAP are $20,000 per connector per target application.

Rich Niemiec, CEO of TUSC, a Chicago-based Oracle partner, is bullish on the new Warehouse Builder offering.

"The biggest benefit is the ability to easily integrate data from internal and external heterogeneous sources with one tool and one company," Niemiec said in an e-mail. "Oracle is providing one tool for multiple functions, which provides consistency across teams and a reuse of skills and processes. Connectors for Oracle E-Business, PeopleSoft and SAP are a huge benefit for partners."

The new Warehouse Builder release eases deployment and scheduling, providing many more options than it did previously, and helps execute the data integration processes, Niemiec added.

Another perk is the product's ability to automate management of slowly changing dimensions for business intelligence. "You can store current and historical data," Niemiec said.

Oracle's new tool also reflects a trend in which the worlds of data warehouses, traditionally used for historical data, and operational databases, typically used for everyday tasks, are becoming more closely linked.

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