![]() ![]() sqlgen project file all your data generation settings and options for that database. ![]() Whichever way you do it, once you’re done simply save into source control your SDG project, to capture in the. Generating test data with localized addresses using SQL Data Generator.Generating realistic dates using SQL Data Generator and Python.How to generate realistic text data using SQL Data Generator.How to start producing realistic test data with SQL Data Generator.I’m going to assume you’ve read some of the previous articles on this topic that described how to generate realistic text, dates and addresses for individual tables in a Customers database, such as: This strategy can range from just accepting the ‘default’ data generated by the tool to using advanced regexes to generate fake data that is almost indistinguishable from the real data. SDG takes care of inserting it in the right order, and the other complexities of interdependent data.Īlternatively, you can just let SQL Data Generator generate the data for you. If you have an existing database, then you can use BCP to export the table data, and then use SDG to import that data, after whatever obfuscation or cleansing you do to it. If you already have some dummy test data, SQL Data Generator can load that from a text or CSV file. Your first task is to use the SQL Data Generator’s GUI to design a strategy for filling each of the tables in your database with data. There is an underlying assumption that you will never need to subsequently alter the test database, because that would mean altering the project file to reflect the schema changes, and for that you need one project file per copy of the database (see Automatically build-and-fill multiple development databases using PowerShell and SQL Data Generator for how to do this). The script uses a build script in source control, to create a copy of the database on the test server, and then the data generator (.sqlgen) project file to fill it with data. First, then, you use the data generator to fill the database with randomly generated dummy data and save the project file and then you run it from a PowerShell script (or alternatively, you can write a command line batch script). You can’t use, or won’t accept the risk of using, live production data to run your tests, so you need to create some fake data, or load pre-prepared data. I’ll show you how to do this using PowerShell, a database build script, and a data generation tool for SQL Server, in this case SQL Data Generator. Let’s say that you need to build a new test database, from the latest version in source control, populate the tables with fake but realistic test data, run the tests, and then tear down the database. He is a regular contributor to Simple Talk and SQLServerCentral. Phil Factor (real name withheld to protect the guilty), aka Database Mole, has 30 years of experience with database-intensive applications.ĭespite having once been shouted at by a furious Bill Gates at an exhibition in the early 1980s, he has remained resolutely anonymous throughout his career.
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