Combine data from sources with different data structures
Sometimes we have systems that contain related data but in different structures
For example a business might use two different CRM systems in different offices (maybe due to a merger etc). Both systems contain information about accounts, contacts etc but the field names and table names are different and the database structures vary. But we still might want to be able to see all of this data in the same place. Or, information like customer details might appear in the accounts system, sales system and manufacturing systems and we want to examine data across the sources.
The data is then available in a standard format to be used by any number of consumer applications.
SQL-Hub Mediated allows the data from each source to be transformed into a Common Schema.
SQL-Hub Mediated manages a set of transformation rules that accurately capture the correct source data for each field and table, for each type of source system.
This may involve field mappings (which field goes where), value mappings (recognising values in different systems that have the same meaning), and any further arbitrary processing and conversion that may be required.
The result is a set of sophisticated, standardised, relational data, from multiple unrelated systems that can be used, analysed and reported on by any number of consumer application regardless of the structure of the source data.
Crucially, SQL-Hub Mediated logs all the transformations for every field for every record so that all the resulting data can be “back-traced“ to the source data.
This means that the transformation process in 100% transparent and each record has a clear provenance.
In addition the transformation process can check the incoming source data for any systematic problems or anomalies and automatically generates audit documentation and full data dictionary and transformation rules documentation.
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