Unlock the Power of Testing in Data Vault 2.0

Testing is vital to any successful Data Vault 2.0 project. It helps you build robust and trustworthy data solutions. In a recent Data Vault User Group meet-up, our Data Engineer, Chris Fisher, spoke on the role of testing in a Data Vault project.

In this blog post, we will provide you with the knowledge you need to understand how a test-driven development approach is beneficial, and how to use it.

Build trust with your stakeholders

Traditional data warehousing approaches leave you waiting for business value. The Data Vault method addresses this by offering an incremental build, allowing step-by-step delivery of business value to users. Test-driven development helps you support the incremental build approach.

Business analysts need reliable data to hold business logic and trust the information. Meanwhile, management requires reliable data to get insights and make informed decisions.

The key to building trust lies in delivering working, risk-mitigated code, software, and data regularly. By adopting a test-driven development approach, you ensure that every step you take is built on a solid foundation.

Test-driven development started gaining traction from about 2003. It aims to encourage simple designs and inspire confidence in code, but how can you apply it to your data warehouse project?

The Test-Driven Development (TDD) Lifecycle

The TDD lifecycle follows a systematic process that aligns software requirements with test cases. This allows for thorough testing before the software is fully developed.

Let’s break it down into five steps:

1. Add a test: Before writing any application code, write a test that meets the feature’s needs.

2. Run all tests: Ensure that all previous tests pass, and the new tests fail, indicating that you haven’t implemented any application code yet.

3. Write code to pass the test: Write the simplest code possible to pass the test, avoiding unnecessary complexity.

4. All tests should pass: Once you write the code, run all tests to confirm that the new code works without breaking any existing functionality.

5. Refactor if necessary: With working tests, you can safely refactor or redesign the code, running the tests again to preserve both new and existing functionality.

Layers of Testing: From Unit to End-to-End

Now that we understand the importance of testing, let’s explore the different layers of testing.

Unit Testing: At the lowest level, unit testing ensures that each function or “unit” within your code is correct. By isolating and testing individual parts of the programme, you can identify and address bugs early in the development cycle. To test various components, check if your programming language has a unit testing library available. For example, Python offers unit-test and pytest frameworks. Additionally, data transformation tools may have integrated column-level tests and assertions. This enables you to confirm uniqueness, nullability, accepted values, and relationships.

Integration Testing: Integration testing verifies the correct functioning of many units working together. This can be applied to various components within the Data Vault structure, including automation and data loading scripts, business vault/business rule logic, and data product/ mart layer logic. For comprehensive integration testing, use an external tool, such as Python Behave. Tools like this implement Behaviour Driven Development (BDD), allowing you to express requirements in plain English using Gherkin Feature Files.

End-to-End/Reconciliation Testing: This focuses on testing the entire data warehouse system from start to finish. While it can be cumbersome, it is essential for data auditability and accuracy. By reconciling data at different stages, you ensure data integrity and build confidence in reports based on accurate data. End-to-end testing can be challenging due to the volume of data involved. However, by using reconciliation techniques between different layers, you ensure data integrity and auditability. This type of testing is particularly valuable for proving compliance, reinforcing confidence in business data, and identifying and resolving errors.

Benefits of Testing for Developers and Users

Effective testing offers many benefits for developers and users alike. For developers, testing promotes clean code standards and identifies bugs early. Refactoring becomes easier, and developers can trust their code at the lowest level. This ensures data reliability and accuracy.

Testing should help users ensure that requirements are met and provides the flexibility to adapt to changing requests. By aligning tests with user specifications, tracking changes, and adopting Agile practices, you can release new features quickly.

Summary

In the world of Data Vault, testing plays a vital role in building trust and delivering reliable data solutions. By adopting test-driven development, implementing unit, integration, and end-to-end testing, and treating Data Vault projects as software development projects, you can ensure robustness, auditability, and user satisfaction. So, embrace the power of testing, and unlock the full potential of your Data Vault project.