Nyalazone’s Dynamic Data Source platform allows the configuration of various transformation rules that are persisted
and subsequently used for iterative data cleansing and transformational needs. The module runs its own proprietary,
in- Memory Database (Data Objects) for storing commonly used data structures that are required for transformation
and cleansing routines. The in-memory processing capability of the module ensure near real-time responses on transformation
needs. DDS facilitates data transformation exercises with various features that allow for very complex rules to be applied
to an attribute or an instance level of a source entity. The unique concept of ‘Computed Columns’ allows for multiple
source columns to be used as inputs for transformation exercises to derive an output column.
Data cleansing and consolidation are facilitated with Fuzzy Logic Matches and Pattern Matches. The platform has the
ability to convert unstructured data to structured data for migration needs. Multiple sources can be joined, correlated
or used for mappings to perform an attribute or instance-level transformation.
