Case Study

Product Data Quality & Taxonomy Alignment 



Large scale, complex content from suppliers and manufacturers must be repurposed for retail websites, catalogues and merchandising, and is often of poor quality—missing facts and figures, misspellings, unusual or conflicting abbreviations, etc.—normalizing and improving this content for the ultimate customer is a major challenge.

Products and normalized attributes need to be organized in relation to each other to enable cross-sell and up-sell.

Migration to new platforms such as Oracle PDQ for data quality needed to be rapidly integrated with product taxonomy for the web.


Mobilized a team of seven skilled taxonomists and immersed them in with the client's new platform team, analyzing product taxonomies against 30+ best practices in structure, labeling, balance of taxonomy as well as fitness for alignment with Oracle PDQ.

Provided Oracle PDQ DataLens building for high-profile product attribute categories, including design of recognition patterns to identify attributes and their values as well as data quality checks of content.

Produced knowledge transfer documentation capturing all the client-specific PDQ rules and actionable alignment with web taxonomies.


Support for completely new business processes to feed product content directly into consuming systems without large-scale, ongoing manual processes to clean the data.

All content touch points that customers rely on are now harmonized and ready for the new web platform, meeting tight deadlines for launch.

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