The Paradata platform consists of a group of foundation architectures as well as a
data-centered integrated infrastructure that powers Paradata SaaS.
We endeavor to adhere to the highest security standards and follow enterprise-class best practices.
New data is constantly added to Paradata’s datasets, acquired from both public data sources and our customers to be harmonized with our proprietary knowledge base.
Paradata’s data management uses an object-oriented framework where entities with attributes represent real world people, things, places, and events. Entities belong to collections called entity sets that reflect a common classification, such as Vendors or Parts or People. Data scientists from both Paradata and our customers define the attributes of interest for each entity set.
These definitions are used to create and organize trustworthy harmonized datasets, resulting in relationally-enabled, attribute-aware datasets that also include a measure of data confidence to support data quality.
For example, we provide tools for a data analyst to examine the original source data from which our master profile entities are created. For supply chain engineers, we offer the ability to drill down and examine the component parts and their detailed attributes to confirm that our quote represents the best decision.
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