Speed Up Test Data Generation by a Factor of 7

Tally Netzer

Tally Netzer

Product Marketing Manager, K2View

Generate synthetic test data quickly and easily by taking 7 key factors into consideration.

Table of Contents


What is Test Data Generation?
Test Data Generation Challenges
Test Data Generation Solutions
1. Speed
2. Cost
3. Quality
4. Security
5. Simplicity
6. Versatility
7. Scale
Business Entities: A New Approach to Test Data Generation

What is Test Data Generation?

Often, testing teams are faced with a lack of fresh, high-quality production data for their tests – and are forced to create synthetic test data based on real data attributes. This is called test data generation. Enterprises that embrace continuous development methodologies have learned that their testing processes are hard to maintain without the ability to generate synthetic test data quickly and easily.

Test Data Generation Challenges

Enterprise testing teams must provision test environments on demand with fresh, high-quality test data. But for real-life production data to become test data, it must be:

  • Complete, fresh, and trustworthy
  • Masked, effectively hiding personal information
  • Populated, to meet the requirements of the development project
  • Synthesized, when additional test data is required
  • Compliant, to address data privacy legislation

Besides the overall lack of clean and available production data, data privacy compliance is a key driver in synthetic test data generation for the very reason that the data is not real.

Recent developments in data privacy regulations are forcing companies to be far more careful in ensuring they do not expose sensitive information through their testing practices. This is particularly relevant in industries like telecommunications and media, financial services or healthcare, which encounter a multitude of Data Subject Access Requests (DSARs) on a daily basis.

Test Data Generation Solutions

Today’s testing teams are tasked with delivering high-quality results, on time, in compliance with privacy regulations, at minimal cost. These demands often lead them to seek test data generation solutions based on production or synthetic data.

Production test data
In this case, the enterprise uses data already in its production databases, processing it to ensure that it is properly masked and subsetted, to comply with legal and organizational requirements. A test data management platform is recommended for test data preparation and management purposes.

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Synthetic data is used when there isn’t enough real data to meet the test requirements.

Synthetic test data
As the name suggests, this type of test data is artificially generated, but closely mimics the attributes of the company’s real data. Synthetic test data, which is used when there is insufficient production data, is safer in terms of privacy compliance and data governance.

When choosing a test data generation solution, consider the following 7 factors:

1. Speed

Will the chosen approach enable you to provision data faster? How much time will you save? Synthetic data can often be provisioned more quickly since it doesn’t require access to multiple systems in production. And when the data is no longer needed, it can be discarded without worrying that it might expose any user information.

2. Cost

A solution is only really effective, when it’s cost-effective. Enterprises must always consider the bottom line and measure the ROI of their chosen technologies. A test data generation solution that both prepares and masks real data received from production, on the fly, can be doubly efficient.

3. Quality

It’s not just a matter of producing test data faster, and at a lower cost. You want your test data to be high-quality, and up-to-date. You also want the test data to maintain its referential integrity. You want a test data generation solution that delivers consistent and accurate results.

4. Security

As mentioned, data privacy issues top organizations’ list of priorities for a reason. Real-world data that might expose users’ information puts everyone at risk and requires meticulous masking procedures. Any masking hiccups might result in stiff penalties, as well as damage to your reputation.

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Agile development requires simple, self-service test data generation.

5. Simplicity

A user-friendly test data generation process helps enterprises reach their test data goals more easily. A self-service solution allows testing teams to provision data independently, without having to rely on one centralized system that only a few can operate. In the era of agile development, this is a must.

6. Versatility

Different testing environments demand different data formats, and the test data generation system’s ability to adjust accordingly can help cut costs and prevent delays. The more adaptable your test data generation system is, the easier you’ll find it to match testing needs like population volumes, verticals, CI/CD pipelines, and more.

7. Scale

Test data generation at enterprise scale is another critical capability. Production data is spot on, but needs to be adjusted, which can take time. Synthetic data may be a bit less accurate, but comes in a wide range of data types and formats, provisioned to suit your needs.

Business Entities: A New Approach to Test Data Generation

Consider a test data generation approach based on business entities (e.g., customers), where the data schema unifies all the entity’s data attributes, across all systems. The test data from these business entities, when persisted in a test data warehouse and synced to all production sources, can be delivered to any testing environment in real time.

Entity-based test data is:

  • Up-to-date – with entities constantly being updated from production

  • Safe – with test data masked on ingestion, assuring privacy compliance and protection

  • Trustworthy – with referential integrity an integral part of every entity schema

  • Divisible – with subsets based on different parameters, for real-time data provisioning

  • Available for use – with test data ready on demand, via API or self-service portal

Entity-based test data generation solutions are used by some of the largest data-centric enterprises in the world.

See for yourself.