The DataLens™ System uses patented technology to understand product data at the semantic level, which enables our highly scalable Data Service Applications to rapidly assimilate, transform, and restructure product information throughout the enterprise as needed — on demand.
Browse the following real-world examples, and see 'Before and After' snapshots of complex product data that has been transformed by a single pass through our DataLens System.
As you review these examples, ask yourself how you would perform these transformations and how much effort and expense that method would require.
Industrial Supply: Motors
Take cryptic, highly abbreviated text and standardize, classify, extract attributes, and translate it into Spanish and Russian.
Office Supplies: Binders
Standardize descriptions and extract attributes from complex non-standard description.
Consumer Goods: Digital Cameras
Extract over 50 attributes from free-form text descriptions collected from vendor websites.
Electronic Components: Resistors
Standardize, classify, translate and extract attributes from cryptic, highly abbreviated text.
Industrial Supply: Fasteners
Classify, standardize and extract attributes from Intelligent Part Numbers (IPNs).
Catalogs: Cables
Extract attributes, classify and create readable descriptions in 8 languages from cryptic, highly abbreviated text.
Free-form Text: Land Title Documents
Extract critical information from unstructured, free-form text documents (Word, et al.).
