How do you estimate data warehouse testing resources?

1 Assess the data warehouse requirements

The first step to estimate data warehouse testing resources is to assess the data warehouse requirements, such as the data sources, the data models, the data transformations, the data quality rules, the data loading frequency, and the data consumption methods. These requirements will help you define the scope and objectives of the testing, as well as the test cases and scenarios that need to be covered. You should also review the data warehouse documentation and design specifications, and consult with the stakeholders and developers to understand the expectations and assumptions of the data warehouse project.

2 Choose the testing tools and techniques

The next step to estimate data warehouse testing resources is to choose the testing tools and techniques that suit your data warehouse project. There are different types of testing tools and techniques available for data warehouse testing, such as ETL testing tools, data quality testing tools, data validation testing tools, data comparison testing tools, data visualization testing tools, and data mining testing tools. You should evaluate the features, benefits, and limitations of each tool and technique, and select the ones that match your testing objectives, budget, and timeline. You should also consider the compatibility and integration of the tools and techniques with your data warehouse environment and infrastructure.

3 Estimate the testing effort and duration

The third step to estimate data warehouse testing resources is to estimate the testing effort and duration based on the scope, objectives, tools, and techniques of the testing. You can use different methods and models to estimate the testing effort and duration, such as function point analysis, use case point analysis, test point analysis, or COCOMO model. You should also factor in the complexity and variability of the data, the dependencies and risks of the testing, the reusability and automation of the test cases and scripts, and the feedback and review cycles of the testing. You should also account for the contingency and buffer time for any unexpected issues or changes during the testing.

4 Allocate the testing roles and responsibilities

The fourth step to estimate data warehouse testing resources is to allocate the testing roles and responsibilities based on the testing effort and duration. You should identify the skills and competencies required for each testing role, such as data warehouse tester, data analyst, data quality engineer, data visualization engineer, or data mining engineer. You should also determine the availability and capacity of each tester, and assign them to the appropriate testing tasks and activities. You should also define the communication and collaboration channels among the testers, as well as with the stakeholders and developers.

5 Monitor and adjust the testing resources

The final step to estimate data warehouse testing resources is to monitor and adjust the testing resources as the testing progresses. You should track and measure the actual testing effort and duration against the estimated testing effort and duration, and identify any gaps or deviations. You should also evaluate the performance and quality of the testing tools and techniques, and the testers, and identify any issues or challenges. You should also solicit and incorporate the feedback and suggestions from the stakeholders and developers, and implement any changes or improvements to the testing process. You should also update and revise the testing resource estimation as needed, and communicate the changes to the relevant parties.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?