Architector Data Governance Components
Architector provides the tools to quickly bring data under control, and get everyone onto the same page concerning the data that is important or vital to your organisation. Central to the toolset is the comprehensive semantic business glossary. Semantic relationships are automatically extracted directly from data definitions, and the quality of definitions is monitored using system and custom rules.
The metadata catalogues are where the things like applications (systems), datastores, processes, and physical data that make up the data lineage are defined. There is also a catalogue of data Issues. The process catalogue implements a process hierarchy, so that relationships between business processes and technical processes can be depicted on the data lineage.
The structure diagram visualises the definitions in the glossary as a formal concept model. Now anybody that can define data can produce meaningful and consistent data concept models! And the definitions and corresponding models are automatically aligned.
The business terms, associated metadata, and all the lineage relationships are stored in a graph database. Graph database technology provides maximum scalability and deep analysis features. The Architector lineage diagram builds on top of the graph database to provide sophisticated and intuitive views of and interactions with the data lineage, to support impact analysis, root-cause-analysis (RCA), etc.
The workflow area provides a way for data teams to define and track the progress of repeating data tasks, which in turn allows managers to understand how effectively the Data Policy is being implemented.
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Components in more detail
Semantic Glossary & Business Rules
Central to the toolset is the comprehensive semantic business glossary, where business concepts and data are defined. Semantic relationships are automatically extracted directly from data definitions, and the quality of definitions is monitored using system and custom rules..
Data Concept/Structure Modeller
A data concept model diagram is an invaluable aid for a definition team, and is an extremely useful communication tool, both within the data community and even to a wider business audience. Architector allows definition specialists to create compelling and meaningful concept models directly from definitions..
One of Architector’s tenets concerning data lineage is that data only changes or moves because of a process. Therefore, Architector maintains a catalogue of the processes that are part of the data lineage. The process hierarchy is one thing that sets Architector apart from almost all other data lineage tools..
Data Lineage Builder
Data lineage comprises of related data assets. Assets and relationships can be loaded from external metadata management tools. The Lineage Builder component of Architector provides an interactive tool to manually create or patch data lineage.
Data Lineage Graphs
Architector is designed to draw meaningful and insightful data lineage graph diagrams. Graphs are drawn automatically from the metadata repository, and users can control content by using the various filters and other options on the control panel..
Architector allows the data team to maintain central catalogues of things that make up data lineage. The main lineage catalogues are: data terms, processes, physical data, data stores (or ‘interface files’), and applications (or ‘systems’).
Data Policy & Procedure Workflow
Architector’s workflow engine also provides tools to define and manage the processes and tasks involved in developing data lineage. In fact, the workflow engine can be used as a general workflow management tool, which the data team can use, or any team can use..
Metadata Reporting Engine
Architector provides direct access to all the metadata in the system via its integrated reporting engine. This allows the user to interrogate and filter through the database for information of interest. Results can be viewed online and also downloaded to CSV or spreadsheet.
Harnessing Innovative Technology
Architector utilises leading edge technology to simplify and extend the capabilities of data lineage management. Technology used includes:cloud technology, natural language processing (NLP), graph database technology, and (soon) Hadoop.