Silver Creek Systems

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Editor’s note: another installment in an ongoing series where the Hub Designs Blog profiles companies and solutions which are relevant to master data management (MDM).

Silver Creek Systems

Company & location: Silver Creek Systems, headquartered in Westminster, Colorado, provides automated data mastering solutions which enable enterprise-wide standardization and integration of product information.

Value proposition: I recently had a briefing with several Silver Creek people. Their core product, DataLens™, applies semantic technology to standardize, enrich, match, repurpose and govern product information. I think of it as data quality for product information on steroids.

The semantic approach makes a lot of sense. I remember from my ERP days how painful dealing with product information can be (requiring endless massaging in Excel or complex SQL queries to extract and reformat it). Silver Creek seems to have an intelligent solution to one of the thorniest issues in MDM.

What point in MDM lifecycle: if your MDM initiative involves product information, you’ll quickly find out that Product MDM is very different from Customer MDM. It’s common for product data to have dozens or even hundreds of required attributes. The hierarchy management requirements for product data are typically more complex. And because a lot of product data is unstructured or semi-structured, you need a specialized parsing engine if you want to automate the standardization of your data.

Relevance to MDM: data quality tools designed for customer information have a hard time handling the widespread variability of product data, its relative lack of structure, the dearth of referential data from third-party sources, the overloading of the “description” field, the classification and categorization requirements and the added complexity in hierarchy management.

As I do more work in the Product MDM area, I’m impressed with Silver Creek Systems and its DataLens solution.

Update on 04/14/09: Silver Creek Systems announced today that its DataLens™ System was named the top Data Quality product by SearchDataManagement.com’s 2008 Products of the Year program. The awards were judged by a team of industry analysts and consultants and presented by the editors of TechTarget’s Enterprise Applications Media Group. For more information, please visit http://www.silvercreeksystems.com/PR_SDMPOY2008/.

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5 Comments on “Silver Creek Systems”

  1. Preston 04/23/2009 at 12:42 pm #

    Dan, we spoke on the phone about a month ago. In regard specifically to product data for MDM, any comments on the ability of automated solutions such as Silver Creek’s to deal with the issue of inadequate attributes? In other words what is to be done if the existing descriptions in various fields do not contain all the information necessary for the parsing engine to populate the appropriate attribute fields? What do you see as the appropriate interplay between automated solutions such as DataLens and subject matter expertise-based manual solutions?

    • Dan Power 04/23/2009 at 12:57 pm #

      Hi Preston,

      With regard to Product MDM, I think there are going to be some situations where an automated engine like Silver Creek’s DataLens is going to be able to handle it, and then there will be exceptions that the engine can’t handle that will have to be routed to a data steward in the business, who may have to research the situation further and then update/correct the product master data. So if things can’t be imputed or calculated from other attributes, old fashioned human research is definitely needed.

      Best regards — Dan

    • Martin Boyd 05/14/2009 at 6:08 pm #

      Preston,

      As you obviously know, inadequate information is a common problem in product data. In some cases all the information you need is right there in the record and just has to be extracted and standardized – and the DataLens System has world-leading capabilities in that regard. However in many cases the data has significat ‘holes’ in it. In this case the DataLens System has a couple of alternatives;

      1) Data can be extracted from external data sources and used to enrich the target record. The DataLens System can pull data frm any external source, legacy system, subscription feed etc. Differently fotmatted/standrdized information is not a problem ans the DataLens System can extract and transform it as part of the operation.

      2) If no electonic information is availbale at all, product records will be flagged as exceptions and sent ot the Governance Studio which is a dedicated interface for data stewards/product specialists to interact directly with the data and enter missing pieces of information. It is even posible to direct these exceptions to external contractors (such as India-based services that can fill-in the gaps – typically at a much lower cost than if the had to work on the whole record)

      Product data is notoriously messy and even the best automation cannot create something out of nothing, however the DataLens System is built from the ground up to deal with these issues and provides a great set of efficient workarounds. No matter the approach you take, you are likely to have a much more cost-effective result than with the traditional altrenatives.

      – Martin Boyd, Silver Creek Systems

  2. Dan Power 05/15/2009 at 10:27 am #

    Thanks for the great comment, Martin – and for pointing out how Silver Creek’s DataLens handles the difficult scenarios that come up when dealing with product data.

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  1. Silver Creek Systems Acquired by Oracle « Hub Designs Blog - 01/04/2010

    […] first profiled Silver Creek in April 2009, and my first hunch that they might end up getting acquired by Oracle came with the announcement […]

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