It’s undeniable that the process of ETL plays an integral role in data integration. But there’s more that goes into ensuring this process is effective than it may seem. That’s where ETL testing comes in.
ETL moves data in three distinct steps from one or more sources to a separate destination. This could be a database, data warehouse, data store, data lake or any other application. Here’s a breakdown of each step in the process:
- Extract: This is the first phase of the process, where data is collected from one or more data sources. It is then held in temporary storage while undergoing the next two steps.
- Transform: During this second phase, data is processed to make its values and structure conform consistently with its intended use case. It aims to make all the data fit into a uniform schema before moving on to the last step.
- Load: The final phase moves the data that has undergone the transformation into a permanent target system. This could be an on-premises or cloud-based target database, data warehouse, data store, data hub or data lake. The process is complete once all the data has been loaded into the destination.
What Is ETL Testing?
ETL testing is a process that validates your data has gone through the three steps of ETL and been loaded into the target as expected. This level of verification helps ensure that there is no data loss and the data you move maintains good data quality. It also helps in identifying any duplicate or missing data in your data warehouse.
ETL testing is important to ensure that your data integration process is running smoothly. It also gives you the ability to automate the process of verifying that your data is reaching the source as expected.
How Does CI/CD Help with ETL Testing?
Continuous integration and continuous delivery (CI/CD) automates the build and delivery operations of a data pipeline. A CI/CD pipeline includes the integration operations that developers use to design objects and the delivery operations that deliver the objects to the production environment.
You can automate ETL testing at each level of data pipeline development with CI/CD, be it during quality assurance, performance, acceptance testing or at other stages. This ensures that the data pipeline is reliable and can be scaled and updated without disrupting the integration tasks.
How Can You Incorporate Continuous Testing in a DevOps Pipeline?
Continuous testing is when you run tests throughout each stage of development instead of waiting until the end of the process to test for quality. Traditional testing processes implement testing when software is transferred from one team to another, with defined times for quality assurance. This adds to the time it takes for the software to be fully developed. Continuous testing helps automate the process to get software to market faster. This, in turn, helps accelerate the DevOps pipeline through automation.
How Can You Implement DevOps in an ETL Pipeline?
To implement DevOps in an ETL pipeline, you need to take a few steps. First, you need to configure the environment so that your CI/CD is always accessible. Then, you need to control your test data or make sure it’s synthetically clean. The next step is to pair your CI/CD pipelines with a version-controlling tool and / or a practical test automation suite. Then you can automate your test generation step by step. And finally, you need to enable feedback loops for instant feedback on quality.
What Are the Best Practices for ETL Testing?
ETL testing can be done as part of your overall data integration process. Here are the best practices to follow for ETL testing:
- Identify and categorize your tests: Determine which ETL tests can be automated and by what frequency, and what skillset is required. Then identify which ETL tests need to be run manually. Categorizing them in this way from the start will set you up for success.
- Set up automation: Use your categorization from the first step to organize your ETL tests into groups. Set up as many as possible to run on automation.
- Run multiple tests at once: Run multiple ETL tests at the same time to increase the overall speed of your testing program.
- Start simple: Get your simple ETL tests up and running and then move on to the more complex scenarios to automate.
- Ensure a clean testing environment: To get the most accurate results, make sure you’re setting up your ETL tests in a clean environment so they are not influenced by others. This might mean creating a temporary environment.
- Put version control in place: Perform root cause analysis when issues arise to make sure they don’t stem from a previous release using a version control system.
- Enable single-click code migration: An automated process like single-click code migration can make it easier to migrate code between environments.
- Put a CI/CD pipeline in place: Use a CI/CD pipeline for ETL testing to make sure your code changes move successfully through automated testing cycles and into staging and production.
- Secure your CI/CD pipeline: Protecting your CI/CD pipeline from security threats is key because the pipeline has access to your data, apps, credentials, etc.
- Create a central code repository: Use a repository as a central location for your ETL testing source code for timely updates and syncs.
- Establish continuous learning: Apply learnings from previous projects to avoid similar issues in the future.
- Limit CI/CD pipeline to a one-way mechanism: Ensure that your CI/CD pipeline is the only thing running in your process chain to avoid failure.
- Put continuous feedback in place: Use a continuous feedback loop to ensure your automation tools are functioning as expected and identify any bugs.
- Operate with transparency: Establish transparency throughout your team to make sure everyone understands the status of your ETL testing and feels comfortable collaborating.
- Implement right tooling: Choose ETL testing tools that perform the testing functions you need most.
