Kinaesis Clarity Metadata Visualisation
Sophisticated analytics providing business meaningful, actionable insights, from multiple perspectives on data origins and quality.
Regulations such as BCBS 239 are among many factors that are driving financial services firms to create more and more metadata in the search for better lineage and quality metrics. The challenge is that metadata is "network-like", temporal and has a number of differing perspectives.
Consequently metadata is extremely difficult to present visually and much harder to use as a decision making tool. Attempts to visualise and exploit metadata can all too easily lead to lineage "hair balls" and a lack of accuracy and completeness.
The data lineage "hair ball"
Kinaesis Clarity Metadata lets you see business meaningful, understandable and useful perspectives on data origins and quality.
Kinaesis Clarity Metadata complements existing metadata and MDM assets to provide a consistent, exploitable view of your data across the organisation.
- Integration: Kinaesis consultants will map metadata to a format in which it can be easily visualised, while remaining in sync with your metadata mastering systems.
- Visualisation: Kinaesis are used to looking at metadata and we realise that it can easily become a meaningless "hairball" of links and annotations. We can propose practical and useful visualisation concepts to deliver a clearer lineage picture. And we can leverage our domain experience to configure visualisation outputs.
- Bottom up analysis: Kinaesis have deep experience of risk from both a business and IT point of view. We can work with stakeholders, system owners and if necessary, code to discover the "bottom up" details required in order to get value from your data architectures and practices.
- Interactive Analysis: Explore metadata finding opportunities for simplification and exploitation.
- Diagrams: Report clear views of data lineage up to Regulators, design authorities and the Risk Committee.
- Numerical Measures: Generate formal, repeatable measures of data complexity and process quality to demonstrate progress.
Kinaesis Clarity Metadata Visualisation has the following key components:
- Visualisation Library: Layout, diagrammatic and style capabilities. Produces innovative, clear visualisations.
- Inference Layer: Inference logic draws conclusions about data lineage, mapping data to ultimate sources and simplifying the dependency graph.
- Metadata Format: A simple, standards-based format for representing metadata independently of source systems.
- Adapters: To bring in data from existing assets such as your MDM system, or via user interaction.
Kinaesis Clarity Architecture