Optim Update

Data privacy and data masking are an integral part of Optim as it has been identified through research that many customers will move to another supplier if they feel privacy has been violated.  Masking the data stops the production data from being used in the test environments.  Optim provides an array of techniques to mask the data, most of which are beyond the scope of this post.  To name but a few, masking character and numerica data, random masking methods, using shuffle techniques for masking by way of loopkup values and ysing Optim’s own transformation library.  The methods are available and work but they work well using key propagation.  A database is made up of related records adn in order for data masking to work effectively, all related rows must also be masked.  Optim provides such funtionality in the form of key propagation.

Next up the edit tool makes use of the table editor so that the user can edit data using various techniques, the table editor allows a user to drop into data and change at will, make use of replace all commands and so forth.  However, the referential integrity of primary keys still sand and cannot be altered, even LOB data can be manipulated to some extent and related tables can be manipulated o joins can be created to extract data.

The compare facility is as it says on the tin – a facility that compares data from a source/extract against data in the database, one of the benefits of having the compare facility is that it provides a means to compare data before and after testing has completed.

This completes the Optim overview and highlights some of the main attributes of the product, along with a simple overview of installation and configuration.  Suffice to say the software can be integral to any organisation seriously considering a solution to data growth.

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