dVXAnalytics is flexible
dVXAnalytics was designed to fit into a wide range of event-oriented
applications. Event-oriented data shares
a number of common elements: a time-stamp field, a unique identifier and a set of
of attributes, or measurements. Each attribute adds a dimension to the
data. In data warehouse terminology, this corresponds to a 'fact table' structure.
This structure readily applies to 'complex event processing', a useful framework for working with
operational systems. This commonality means that
dVXAnalytics readily extends to applications that involve automated decision-making.
Application templates extend dVXAnalytics
Application templates are meta-data structures that transform data from an domain-specific
format into one that can be directly imported into the platform.
Application domains range from internet API's to customer transaction histories stored in a
data warehouse.
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