Data Quality System deals with product data variability.
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Press Release Summary:
Built to adapt product data to customer-driven sales and supply-chain requirements, DataLens(TM) System automates cleansing of incomplete or inaccurate data to ensure optimal quality and compliance to industry and corporate governance standards. Content-in-Context(TM) technology recognizes product data according to its format, content, syntax, and language across tens of thousands of product categories. Semantic-based technology resolves any data incompatibility.
Original Press Release:
Silver Creek Systems Unveils Solution that Guarantees Highest Levels of Product Data Quality and Governance
New DataLens(TM) System with Content-in-Context(TM) Technology Provides Greatest Amounts of Useable Data for Enterprise Applications and Online Retail Sites
WESTMINSTER, Colo. - September 18, 2006 - Silver Creek Systems, a pioneer and leader in enterprise product data quality solutions, today announced the newest release of the DataLens(TM) System, now with Content-in-Context(TM) technology. DataLens is the only data quality system built from the ground up to adapt product data to today's customer-driven sales and supply-chain requirements. Applications, from online retail to Product Information Management (PIM) and Master Data Management (MDM) system consolidations plus all aspects of the supply-chain, rely on consistent, high-quality data - data that is often incomplete or inaccurate and therefore requires significant manual effort or custom coding to "cleanse." The DataLens System automates this process for the first time, ensuring the highest levels of product data quality and compliance to industry and corporate governance standards. In fact, the DataLens System is the first and only data quality solution developed to deal effectively with the inherent complexity and variability of product data.
"Companies have always spent money on data quality," said Colin White, president of BI Research, a Portland, Ore.-based industry analyst firm. "But, while there have been good software solutions for customer data, product data has been much harder to address and has been more manual in nature - but that's changing. We're now seeing more product-based projects, and, with them, a growing recognition that product data presents different problems from customer data, and therefore requires additional data-quality capabilities. Most traditional approaches are pattern-based, but a product data quality solution requires a deeper semantic understanding of the data - something traditional tools don't usually address."
Product data resides in a variety of corporate systems and applications from PIM, MDM, supply chain, ERP, inventory, procurement, data warehouse, retail and others. As the data is shared and moved among systems, any inconsistency and/or non-compliance to standards become apparent. These problems are exacerbated by a number of factors: 1) the growing volume and complexity of data in disparate systems, 2) the move to online commerce and information sharing, 3) greater regulatory requirements, 4) increasing competitive pressure, 5) the need for real-time information, 6) higher customer expectations, and 7) activities such as mergers and acquisitions.
"Historically, companies dealt with product data problems by hand, or by writing custom code," said Martin Boyd, vice president of Marketing for Silver Creek Systems. "These methods are slow, expensive and ultimately not scalable. The DataLens System automates product data quality solutions for the first time, delivering cleaner, more consistent and validated product information for use throughout the business."
Silver Creek's DataLens System uses semantic-based technology to resolve data incompatibility and deliver usable data in any required form - standardized, localized and enriched. Traditional data quality tools have proven inadequate to handle the complexities and lack of standardization typical of product data. As a result, IT takes months to adapt these tools to new product domains.
Further, these tools are stymied by the infinite variety of ways that data can be presented-ambiguous, variable and not standardized in content or format. Consider a product description of a motor: to the human brain, "10hp ac motor" and "motor, 10 horsepower, alternating current" describe the same motor, but traditional data quality tools don't have the same level of sophistication. The DataLens System "understands" data like a human expert, putting product data in its natural context. Silver Creeks' DataLens System, with its semantic-based technology, allows it to "learn" new product domains from subject matter experts who use the system. The result is more useful data for businesses and their customers, in less time, and at a lower cost.
Behind this capability is Silver Creek's patented Content-in-Context technology. Content-in-Context recognizes product data according to its nature - format, content, syntax and language, across tens of thousands of product categories. Content-in-Context technology identifies and extracts data meaning in context, and it insulates the system from variances in word order, abbreviations, spelling and punctuation. Content-in-Context also has inherent data governance capabilities that enable users to import industry and corporate standards to be used by DataLens to compare incoming product data, and identify and reject incomplete or false information.
When used in combination with MDM and/or PIM systems, DataLens significantly enhances the performance of the application by improving the quality of the data entering the system. For a major office supplies distributor with more than 300,000 constantly changing inventory items, DataLens standardized product descriptions and extracted attributes for improved search navigation, making customer searches less frustrating and therefore boosting customer satisfaction and sales. For a major global electronic components distributor, DataLens standardized product descriptions and significantly improved the match rate between available inventory items and incoming customer quote requests, boosting monthly sales quotes by millions of dollars.
"In our industry, product information is constantly changing and is never in a consistent, standard form, so our ability to absorb and manage that information better than anyone else gives us a significant, competitive advantage," said James Underhill, senior vice president of Accounting and Information Systems for McJunkin Corp., a privately held, West Virginia-based distributor. "We looked for a long time to find a reliable, scalable solution to automate our product data processes, but did not find an acceptable one until we met Silver Creek Systems."
"We are breaking new ground in how product data is handled and leveraged as a corporate asset," said Barbara Mowry, president and CEO of Silver Creek Systems. "Our customers can automate tasks that could never before be automated - cutting out cost and time and increasing revenues while improving the quality of the information available for critical processes all across the business."
About Silver Creek Systems:
Silver Creek Systems, based in Westminster, Colo., is the leader in enterprise product data quality and governance solutions. The DataLens(TM) System is the only data quality solution built from the ground-up to effectively adapt product data for use in mission critical enterprise applications. Based on breakthrough semantic Content-in-Context(TM) technology, the DataLens System can understand, match and publish inconsistent product information into any required form, in any language and in real-time for any enterprise application, including manufacturing and distribution, E-commerce, Product Information Management and Master Data Management applications. For more information, visit www.silvercreeksystems.com
