To establish a complete view of the data management landscape, either across systems or within a given domain, organizations are modernizing metadata management through the use of data cataloging and data governance tools. However, these systems alone do not capture the full breadth of metadata and all of its variations across applications, domains and data platforms.
Knowledge graphs provide the ideal medium to integrate and harmonize metadata from multiple systems – striking a balance between establishing common metadata models and retaining the nuance and richness of individual data domains. Support for models described in SKOS and OWL provide common starting points for enterprise metadata models.
Anzo makes onboarding and harmonizing metadata from different sources rapid and easy and provides configurable dashboards to explore and analyze metadata. Most importantly, as the data landscape grows, metadata management requires an enterprise-scale knowledge graph that Anzo uniquely provides.
This blog explores the relationship between data management and AI in the context of knowledge graphs, and offers practical considerations to get started building an enterprise scale knowledge graph.
Leveraging Semantic and Graph Technology to Tame the Enterprise Data Storm
This white paper describes the rapidly evolving business and regulatory drivers leading financial services organizations to implement vital new enterprise-wide data technology initiatives, and why legacy data management tools can no longer keep up.
Clinical Data Standards Management
Learn how this large pharmaceutical company simplified and accelerated compliance with federal and international regulatory mandates
Harvest metadata from applications, metadata repositories, or catalogs across the organization and connect or collect it into the knowledge graph
Map related metadata from separate sources into a common model using semantics and graph and based on enterprise standards
Build visualizations and analyze the metadata to understand everything about your information including where it is, who owns it, how clean is it, how often is it used, and more.
Publish clean integrated sets of metadata that conform with corporate standards to IT teams, data stewards, and others across the organization to enable best practice data sharing, collaboration, and usage.