The Semarchy Convergence for MDM Data Certification Framework transforms source records pushed to the hub by publishers (source applications or direct data authoring), into consolidated and certified Golden Records. This process is automated and involves several phases, generated from the rules and constraints defined in the model. This framework enables the fastest time to production for MDM implementations. It allows you to start with a tactical approach and iteratively involve the business users to create a positive synergy that drives your strategic data governance over time.
Enrichment and Standardization
The data certification framework uses enrichers to normalize, standardize and enrich source data pushed by the Publishers into the hub. Using enrichers, data from the various source publishers is brought to a level of completeness that makes it suitable for creating the master data.
Data Quality ValidationSeveral types of data quality validations are supported, including referential integrity for relationships, unique keys, mandatory attributes, list of values ranges and complex validations. These validations can be executed at various stages of the data certification process. Records not meeting the quality standards are isolated and preserved for review by the data stewards. |
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Powerful Matching Features
Duplicates are detected as part of the certification process. Matching is a highly-optimized process that can be entirely customized for each entity using complex expressions. This matching allows de-duplication for any type of entity designed in the hub.
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Record-Level or Attribute-Level ConsolidationDuplicates detected are consolidated as golden records as part of the certification process. Consolidation can take place at record level or attribute level. A variety of strategies is available for consolidation, including value frequency, value completeness, preferred source, length, etc. |
Model-Driven Data Manipulation Language
The rules driving the data certification can be expressed in a model-driven manipulation language, SemQL. With SemQL, you can simply create enrichment, validation, matching or consolidation rules using the business terms defined in the model.
Extensible Capabilities
Semarchy Convergence for MDM allows extending its enrichment, validation and matching capabilities using the Open Plug-in Architecture. Using this architecture, you can leverage third party products or services such as Google or Yahoo Maps in the data certification process.
Address Matching Using Convergence for Address Verification and Geocoding
The Convergence for Address Verification and Geocoding option provides highly accurate worldwide address enrichment, standardization, geocoding and verification with a cost effective approach. It enables users to create full postal addresses from partial ones, validate and correct address elements to street level for most countries.