What can be achieved with Metadata Manager?
The Adaptive Metadata Manager provides foundational capabilities that enable organizations to understand risk, manage compliance mandates properly and document and track where their data is stored, what their data means and how their data moves across their organization. This involves providing the governance processes to manage ontologies, nomenclatures and definitions, and linking their terms to the various business and technical metadata concepts that ensure agility in response to business requirement change.
Harness the amazing business potential of your metadata to capture and manage all the valuable business, operational and technical metadata stored inside ‘systems of record’, ‘systems of engagement’ and ‘modeling tools’ within your organization. Adaptive have developed a highly capable, extensible and industry-leading metadata management platform.
Your metadata has amazing potential for enhanced analytics, enterprise search and discovery and ensuring proper governance is in place. Adaptive provides a data governance solution to help you realize that potential.
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World class repository technology with a number of leading methodologies, frameworks and domain expertise.
Capture data definitions and lineage from:
Business and IT developments in the areas of:
Clients to fully leverage their enterprise information and enterprise architecture investments. Interoperability and openness are central to our approach.
OEMs and ISVs to build upon the capabilities of the Adaptive foundation repository to increase the value of their own software products.
Consultancies to enhance their services delivery, licensing the use of Adaptive proprietary IP in their own customer engagements.
In addition to facilitating knowledge-sharing and better decision-making enterprise-wide, the Adaptive Metadata Manager:
- Establishes a common language between business and IT;
- Improves data quality through a greater understanding of enterprise data;
- Enhances business intelligence and consistency among data elements;
- Reduces data redundancies;
- Greatly improves knowledge transfer and alleviates exposure when personnel transfer, retire or leave the company;
- Decreases development cycle times for new and existing systems; and
- Improves efficiencies of data analytics.