What is traditional test data provisioning?
Effective software testing depends on the test data that is of high quality and compliant. However, getting this data may be time-consuming and have errors, too.
In traditional ways, data engineering teams have been playing an important role in data sets. Their major role is to prepare and provision test data sets. Then, software teams use those data sets to test the software in various scenarios.
Data engineering teams use test data preparation tools to perform various functions. For example, teams use them for formatting, scrubbing, data extraction, and masking to keep sensitive information safe. As well as these tools deliver the data to the targeted lower environments.
On top of that, data teams receive significant test data requests. So, it’s tough to meet SLAs.
Test data generation requires technical expertise, and this is the reason to call the data engineers for this. These professionals are well-equipped in this domain. They have the technical know-how of the source systems, their data types, and hierarchies.
Even though there are many paid test data management solutions, they still require an understanding of different areas to be used. That may include understanding the data sources, SQL, or writing scripts for transformations such as aging and keeping the referential integrity.
What do you think, why does software take so much time to be delivered? Most of the answers would be because of the scarcity of test data. And that’s true. However, this concern is no more since test data is readily available for software developers.
Do-It-Yourself Approach for Test Data Provisioning
Before we start discussing the DIY approach, let’s take a quick look at what is data provisioning.
It is a technique for obtaining, transforming, and delivering data from different sources to meet the specific requirements of users.
Getting the right test data for software testing can be a time-consuming process, right? Agile software teams don’t want to face such delays. However, there are many right tools and solutions at your disposal for test data. Using them makes the test data stakeholders provision data easily without relying on others to obtain the data.
So, modern test data management solutions must be easy to use. That means they shouldn’t demand any technical expertise, such as data engineering or SQL while using them. Plus, there should be a way for testers to explain their test data requirements in clear business language. As a result, they will access the necessary test data within a few clicks.
As an example, they could ask, “Provide me the production data of all the citizens of Texas – who have spent exceeding 40,000$ and are members of our Gold loyalty program – into the quality assurance environment.”
With that, you don’t need to wait for days or weeks for the test data provisioning teams to answer your query. Don’t remember, we’re blessed with the AI era. However, using the self-service tools, your specific test data subsets can be provisioned in no time.
How to streamline the process with test data products?
A test data product approach comes in handy to solve the problem regarding provisioning data.
This approach includes all those things that are important to provision a dataset. It even covers anything in between the higher and lower environments, like data ingestion and delivery, changes and masking techniques, and CI/CD integration via APIs.
When using test data products, users can perform different functions. They can be subsetting, refreshing, aging, reserving, snapshotting, and rolling back. The best part? Users can do that without having any technical knowledge of the source systems.
Different teams of organizations can use this approach. On the one hand, data engineers do their best to configure it. On the other hand, software and quality engineers use it.
Here are the benefits of test data products:
Software delivery takes a short time
When it is easy and simple to obtain test data, software delivery takes a short time.
Improves software quality
With shift-left testing and identifying early code errors or bugs, software gets improved where it is lacking.
Enhances productivity
With more actions in this approach, data specialists focus on more effective work.
Improves the employee experience
Developers and testers can be self-sufficient without relying on others to automate time-consuming tasks.
In a nutshell, test data management depends on test data products. This way, software testers can go for test data provisioning on their own. And when they don’t need any external help, several benefits emerge, like better data quality, swift software delivery time, and increased productivity.