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Technical Information |
VisuaLinks® is a data visualization and pattern discovery tool that can simultaneously
connect to disparate relational databases.
VisuaLinks is designed to be scaleable and flexible with low administrative cost. It can connect to any
relational schema through a server-side, XML-based data view. The VisuaLinks architecture includes three layers –
the Client Layer, the Server Layer, and the Data Layer.
The Client Layer is the end-user visualization component
(the VisuaLinks Client). The VisuaLinks Client is the user interface responsible for the 3-D visual representation
of data relationships and patterns and is the means for data extraction, analysis and output operations. This GUI-based
front-end is also used for system administration, data modeling collaboration, network analysis, rule-based operations
and many other user operations.
The Server Layer (Visual Clarity Server) is responsible
for maintaining database connections, maintaining user connections, maintaining security profiles and storing the
dynamically-linked service components that represent the business logic of the VisuaLinks application. Each of these
service components is loaded during the Visual Clarity Server startup process and accessed by users through requests from the VisuaLinks Clients.
The Data Layer refers to the data accessed by the Visual
Clarity Server. This layer can be made up of any number of relational databases or even other servers that act as
proxies to additional data layers. Access to the Data Layer is tightly controlled by the Visual Clarity Server security
settings. Data access is also limited by the data modeling process which defines the values in your database returned
to users through VisuaLinks Client requests.
VisuaLinks’ integrated service components, including the Disambiguator®, Fuzzy Matcher
and Network Miner, provide an unparalleled set of capabilities to support pattern detection and advanced
data analysis for a variety of applications. To date, VisuaLinks has been used with a host of different domains of
data, such as network traffic, medical patterns, pharmaceutical research, insurance fraud, bank transactions, drug
trafficking, criminal investigations, terrorism, and many more. |
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