What is test strategy in ETL testing?

A test strategy is an outline that describes the test plan. It is created to inform the project team the objective, high level scope of the testing process. This includes the testing objective, methods of testing, resources, estimated timelines, environment etc.

How do you test for ETL?

What are the 8 stages of the ETL testing process?

  1. Identify your business requirements.
  2. Assess your data sources.
  3. Create test cases.
  4. Begin the ETL process with the extraction.
  5. Perform the necessary data transformation.
  6. Load the data into the target destination.
  7. Document your findings.

How do you test ETL pipeline?

Getting ETL testing up and running can seem intimidating and technologically challenging, but it can be boiled down to a set of 7 steps:

  1. Specify business requirements.
  2. Define test cases.
  3. Extract data and run tests.
  4. Transform data and run tests.
  5. Load data into the target database and run tests.
  6. Run end-to-end tests.

What is test data in ETL testing?

ETL — Extract/Transform/Load — is a process that extracts data from source systems, transforms the information into a consistent data type, then loads the data into a single depository. ETL testing refers to the process of validating, verifying, and qualifying data while preventing duplicate records and data loss.

What is difference between test strategy and test plan?

A test strategy sets the general standard for testing activities. A test plan, on the other hand, defines specific details of the QA responsibilities and process.

How do you perform an ETL test?

The typical process to conduct a performance or scalability test is:

  1. Validate performance expectations, gather user demand & business growth statistics.
  2. Build out performance test environment and identify test scenarios.
  3. Develop test scripts and test data and conduct tests.
  4. Performance analysis & reporting.

How do you write test cases for ETL Testing?

ETL Test Scenarios and Test Cases

  1. Validate the source and target table structure against corresponding mapping doc.
  2. Source data type and target data type should be same.
  3. Length of data types in both source and target should be equal.
  4. Verify that data field types and formats are specified.

What is the basic concept of ETL testing?

The basic concept of ETL Testing and Data Warehouse Testing. The answer lies in the understanding of an ETL process. An ETL process at its core reads data, applies a transformation on it and then loads the data. This can be represented by the following simplistic equation. Input Data + Transformation = Output Data.

What does the tester do in ETL data warehouse?

The tester will check the test component of the ETL Data Warehouse. The tester will execute the data-driven test in the backend. The tester creates the design and executes the test cases, test plans or test harness, etc. Tester identifies the problems and will suggest the best solution also.

How to compare ETL test results with target table?

Apply transformations on the data using SQL or a procedural language such as PLSQL to reflect the ETL transformation logic. Compare the results of the transformed test data with the data in the target table. The advantage with this approach is that the test can be rerun easily on a larger source data.

Why is ETL validator used in ETL testing?

This is where ETL testing tools such as ETL Validator can be used because they have an inbuilt ELV engine (Extract, Load, Validate) capabile of comparing large values of data. Example: Write a source query that matches the data in the target table after transformation.