![]() ![]() Detailed data generation settings for each selected table ![]() After that, the window with detailed data generation settings for each selected table appears: You will then see a progress bar showing the table metadata loading. bat file by clicking Save Command Line located on the lower left of the data generation settings window.Īfter you are finished with the settings, on the lower right of the data generation settings window, click Open. Include empty values (10% of rows by default).Include NULL values (10% of rows by default).You can set the value distribution mode in one of the following ways: You can also clear data before generation by setting the Truncate data from table before generation parameter. By generation of data by time (10 seconds by default).By proportion of existing data in the volume of percent (10 % by default).By specified number of rows (1000 rows by default).Note that you can generate SQL test data in different modes: Next, on the Options tab, set the options of data generation for the database: In the Data Generator Project Properties window that opens, on the Connection tab, you can see the current MS SQL Server instance and the database selected for data generation, which can be edited (if necessary). Running the Data Generator for SQL Server tool in dbForge Studio If you are using dbForge Studio, on the main menu, choose Tools > New Data Generation: ![]() Running the Data Generator for SQL Server tool in SSMS To open this component, right-click Data Generation > New Data Generation against the necessary database in SSMS: Apart from this, the relationships between tables are also taken into account, as the process of data generation depends on them. It should be noted that realistic test data is generated based on column names, dimensions, and data types. The Data Generator for SQL Server tool is integrated into SSMS and is also included in dbForge Studio. Generating data with the help of Data Generator for SQL Server The most convenient way is the population of SQL tables with random data with the help of visual data generation tools. Filling a SQL database with dummy data can be very useful when we want to run some tests. In this article, we will examine the process of populating the employee database with dummy data, whose schema we designed in the previous part. ![]()
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