Product data management includes classification, standardization, elimination of duplicate data, and processes to manage these activities. Mastering product data is different from the regular domains such as customer and vendor data, where standards exist to a certain extent. Product data standards are still evolving, and the complexity and variation within the product data descriptions makes it difficult for traditional tools and approaches to handle the product data management process.
OpenDQ features critical elements for comprehensive product data management:
Unstructured data interfaces
Cutting edge natural language processing techniques enable OpenDQ to identify key product information accurately in structured, semi-structured, and unstructured data
Handles infinite variations in spellings, order of words, abbreviations etc.
Data extraction, transformation, loading for data integration
Extract product data from multiple data systems including data bases, EDI files, Excel worksheet, XML files, CSV files, etc.
Transform, parse product data into any format, and apply complex business rules on the data
Parse or validate data to product data standards such as UNSPSC, 1SYNC, GS1, eClass or other proprietary standards
Integrate data into databases, ERP systems, XML and other applications
Comprehensive Data Quality
Comprehensive data profiling capabilities to identify data quality problems
Highly advanced fuzzy matching capabilities, handle variations in spelling, typos and noise
Dictionary-based standardization with fuzzy matching capabilities for Comprehensive standardization of product data
Advanced De-duplication and Merge capabilities for creating the master product record of reference
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