Silver Creek Systems, a pioneer and leader in enterprise product data quality solutions, announced the newest release of the DataLens System, now with Content-in-Context 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, Oregon-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.
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.
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