There may be a number of steps involved in getting data from the base tables into a format that can be imported into your application database. This layer contains derived tables and views which create data similar to what would be seen in the application that you are testing. The base data layer contains the dummy data tables, any data generation scripts, and a sequence or sequences for generating Ids. These layers can be within different schemas within the database. The solution is broken into a number of layers. Child – Parent relationships are created by including the parent id in a Cartesian product with the child data (See below).ĭiagram 1 - Populating the Application databaseĭiagram 2 - Use of Synonyms where changes to the application database are not allowed. Id values are generated using a sequence. Using the generated dataset this gives 8,000,000 (10 x 10 x 1000 x 4 x 20 x 1) rows of data. datetime, character and numeric.ĭata is generated by creating Cartesian joins on the tables. If you wanted data that was only based on data type and had no other meaning you could classify the tables by data type e.g. Some tables are reused to generate street names and post codes. The scripts below create a number of tables for storing different data descriptors, e.g. The scripts and methodology allow sample data to be generated. The purpose of this article is to provide a means of generating random data which can be inserted into a database for testing purposes. This caused a lot of rework after GO-Live which in turn affected the perception of quality of the project as a whole. We didn’t have enough data to test response times or to tune SQL until after GO-Live. The database was a third party database and the vendor wouldn’t allow data to be entered via the back end. I have worked on a number of projects where there hasn’t been enough data to test reports and extracts and other database applications.
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