Oracle has introduced Oracle Product Data Quality Cleansing and Matching Server, a new offering based on the DataLens System from Silver Creek Systems, a member in the Oracle PartnerNetwork.
Oracle Product Data Quality Cleansing and Matching Server standardizes, matches, enriches and corrects product data from different sources and systems, using patented semantic-based technology to recognize highly variable product data, according to Oracle. By extending Oracle Product Hub with data quality capabilities, Oracle aims to help customers to improve the accuracy, completeness and integrity of their master product data."
"Product data is a very different data domain than other more traditional data domains that data quality technologies handle-such as customer name and address. The differences and characteristics of product data require a different technology approach," Martin Boyd, vice president of marketing, Silver Creek Systems, tells 5 Minute Briefing.
The data is highly variable and so it requires semantic technology to deal with the variability, Boyd explains. "The DataLens technology is built on a semantic approach, and that is what allows it to operate very efficiently with product data and the kinds of data that quite simply choke up traditional approaches." The semantic technology is also "auto-learning" states Boyd. "It can make inferences about unrecognized data so it can learn by itself as a natural or side effect of normal operation. That makes it tremendously efficient."
Oracle Product Data Quality Cleansing and Matching Server can work across any industry, according to Oracle, and can easily adapt to industry-specific product data such as clinical supplies in healthcare, consumer goods in retail distribution, component data in manufacturing, indirect office supplies in public sector or services in telecommunications.
For more information on the Oracle Product Hub, go here. And, for more on Silver Creek Systems, go here.