Metadata Management
What is metadata management?
Metadata management helps standardize a common language and description of data, using a set of policies, actions and software to gather, organize, and maintain it. This makes your data quicker to find, understand, and use by both humans and technology.
Solidatus is a data lineage tool that also functions as a metadata management tool. It supports both automated metadata management and active metadata management by enabling users to easily ingest and store metadata, to view existing metadata for any data element through business metadata lineage, and to query and visually decorate data elements based on metadata that is relevant to crucial business questions.
What is active metadata management?
Active metadata management continually analyses and dynamically updates metadata related to data management, users, systems and data governance reports. It continuously aligns actual sage with the design of data flows. Active metadata management translates analytics into action by generating operational alerts and recommendations. It identifies patterns in data operations, enabling AI-assisted optimisation of metadata utilisation and data workflows.
With our integrators and solutions, Solidatus allows you to continuously scan systems, data and lineage. As Solidatus allows you to apply business context and business lineage on top of technical lineage, to understand if you’re meeting your requirements for cases versus what is actually in your system. Solidatus also has analytics capability and automated alerts to support this practice.
What standards does Solidatus work with?
Solidatus works with multiple industry standards and is flexible enough to support multiple standards including Dublin Core (DC), Data Catalog Vocabulary (DCAT), Resource Description and Access (RDA) and partners with EDM Council to support Data Management Capability Assessment Models (DCAM) assessments. Solidatus is also compatible with OpenLineage as an open standard for metadata and data lineage collection.
More FAQ Topics
Data Flows and Data Mapping
In data lineage, data mapping is the specific process of linking data fields from one data source to others.
Data Management
Data management is the process of collecting, keeping, and using data in a cost-effective, secure, and efficient manner
Data Mesh and Data Fabric
Data mesh is a methodology of managing data, whereby instead of one central data control unit or team, data management is decentralized in an organization
Data Migration
A data migration process involves selecting, preparing, extracting, and changing data in order to permanently move it from one software system to another
Data Risk Management
Data risks for AI relate to regulatory requirements, responsible AI use, and the ability for users to trust the outputs of AI models
Data Tracing
Data tracing refers to being able to trace back from a critical business use case, such as an annual report or compliance requirement, to see the source, journey and changes of data that impact these use cases.
Data Transformation
Data integration tools allow data to flow between different technologies. One of the problems of using a data integration tool is that it might not capture the data flow – and lineage or any transformation that is happening when data moves from one technology to another.
Solidatus Integrations and Solutions
A Solidatus Integration enables Solidatus to ingest detailed information (metadata, lineage, transformations, etc) from external systems into structured models.
Types of Data Lineage
Column-level lineage is a form of lineage that goes to the level of detail of tracing the flow of data through your organization at the column level of a system – as opposed to only the table level.
Newsletter
Subscribe for latest news, blogs and resources.