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Build better product data across the enterprise. Enhance the supply chain. Increased productivity requires high-quality data.

To create an efficient and profitable supply chain, the accuracy and consistency of product and supplier information is crucial. DataFlux solutions allow you to identify and link information about your products and inventory — and build accurate information that you can share across buyers, sellers and distributors.

The DataFlux PIM Solution provides the technology and processes you need to capture and manage consistent, accurate and reliable data about your products. Through a configurable data model, you can create a dynamic repository of product data, which can then feed any ERP, CRM or other enterprise system. 

With the DataFlux PIM Solution, you can:

  • Identify and prevent data defects in real-time to create more accurate records on products and inventory from any trading partner in your supply chain
  • Standardize product names on industry-standard registries such as UNSPSC or eCl@ss
  • Match product or supplier information across sources
  • Identify duplicate product records — and design rules to consolidate or eliminate extraneous data
  • Customize data quality routines to meet your company's inventory or product nomenclature and protocols
  • Reconcile accounts payables and accounts receivables to ensure accurate billing and payment processes

The DataFlux PIM Solution is part of the DataFlux master data management (MDM) strategy. Organizations can design customized business rules to identify trends in product data (item numbers, product descriptions, etc.).  These rules can normalize and standardize any data to create a unified view of product and supplier information.

Data Quality Integration Solution for a Product Data Management
Supplier, partner or other data containing product information comes into the organization. DataFlux appends product data with industry-specific classifications or customized standards to generate unique product codes. Usable product code information can now be used for spend analysis, inventory maintenance, and other activities that rely heavily on non-name and non-address data.