![]() ![]() ![]() Each test case should output a ‘pass’ or ‘fail’ result, based on your pre-defined specifications. Test data is usually stored in a test data warehouse.Įxecute the tests – Now you’ll need to run the tests and evaluate the results. Here, you can assign records, which match certain criteria, to each test. ![]() This is because ETL rules can easily define output names, variables, and default values for each node.Ĭreate a test mart – You must match the correct data to the correct test case, which you can do using a ‘test mart’. A data generation engine can produce synthetic data required for testing, again using your workflow model. Generate the data required for the test cases – Once you’ve created all of the test cases, you’ll need to apply data sets which cover all of them. You can do this automatically, generating test cases which use every combination of inputs and outputs, and covering every possible path through the model. However, it’s important to remember to create a workflow model before starting your ETL process.ĭerive test cases from your model – Since each of the stages in the flowchart are ‘If, then’ statements, you can easily transform each path through the workflow into a test case. This could be in the form of a flowchart, following the logical stages of the data pipeline from beginning to end. While it requires a certain time investment, formal modeling of your workflow can prevent or mitigate many issues which can occur further down the line. Choose your ETL testing automation tool – This could be a ready-made platform, or a manual programming language with powerful database drivers, such as Selenium or Java with JDBC (Java DataBase Connectivity).Ĭreate a workflow model – The process of developing an ETL workflow is often ad hoc, and based on trial and error. ![]()
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