We are in the middle of acquiring the tool. We have successfully completed a PoC with the tool, and we are in the process of onboarding it for a customer. There were two major use cases. The test data masking and test data generation part was one of the major use cases for which we tested the tool. Integration within CI/CD pipelines was another major use case.
We have several development teams within our department using the solution to create test data to test the storage for all kinds of data from our company. We can't use actual data for testing because of privacy, so we create synthetic data using DATPROF. We have one department with about 20 teams mainly using the solution on virtual machines. They are all connected to one central SQL server database in which the data is generated. We are a transportation company and all the data we deal with is regarding trains.
We are using DATPROF Privacy and DATPROF Runtime for masking sensitive test and development data on Oracle, SQLServer, MySQL, and Postgres databases. The main purpose for using this solution is to be compliant with GDPR (General Data Protection Regulation) and for protecting sensitive business information.
Test Consultant at a tech company with 51-200 employees
Real User
2021-07-05T13:00:00Z
Jul 5, 2021
Cost reduction and time-to-market targets were the starting points of our implementation. Subsetting an anonymous, but large production database into a manageable size, thereby reduced storage costs for our test environments. By shrinking the database to an easily portable database, we can refresh test databases swiftly for regression testing purposes. For our customers, it is also a way to start the transition towards a flexible cloud/container-based test environment to meet our CI/CD targets in the future.
We are using a standard software solution with some custom adjustments on an IBM DB2 LUW database. One of our main goals with Datprof's software was to reduce the required data storage by means of subsets. A test database where we previously used a production copy required 23 TB of disk space. By subsetting to a database with the (anonymized) data of 30,000 customers, the disk space has been reduced to only 130 GB. By using the tooling, we therefore only use 0.5% of the original amount of disk space.
The solution is used for: 1. Subsetting test data from/to databases with an incomplete relational model. (With homemade tooling it wasn't possible.) 2. Higher management demanded testing to be done with masked data
DATPROF primarily offers capabilities for subsetting test data, masking sensitive information to comply with GDPR, and generating synthetic data for testing environments.
DATPROF enables companies to reduce storage costs, anonymize data, and seamlessly integrate within CI/CD pipelines. It supports databases such as Oracle, SQLServer, MySQL, Postgres, and IBM DB2 LUW, ensuring the protection of sensitive business information while creating test databases. The tool also provides...
We are in the middle of acquiring the tool. We have successfully completed a PoC with the tool, and we are in the process of onboarding it for a customer. There were two major use cases. The test data masking and test data generation part was one of the major use cases for which we tested the tool. Integration within CI/CD pipelines was another major use case.
We have several development teams within our department using the solution to create test data to test the storage for all kinds of data from our company. We can't use actual data for testing because of privacy, so we create synthetic data using DATPROF. We have one department with about 20 teams mainly using the solution on virtual machines. They are all connected to one central SQL server database in which the data is generated. We are a transportation company and all the data we deal with is regarding trains.
We are protecting our personal and sensitive information, while we provide test data to our customers for their business-as-usual and project testing.
We are using this solution to scramble/mask our personal/business-sensitive information in our test system for MS Navision and the JDE ERP system.
We are using DATPROF Privacy and DATPROF Runtime for masking sensitive test and development data on Oracle, SQLServer, MySQL, and Postgres databases. The main purpose for using this solution is to be compliant with GDPR (General Data Protection Regulation) and for protecting sensitive business information.
Cost reduction and time-to-market targets were the starting points of our implementation. Subsetting an anonymous, but large production database into a manageable size, thereby reduced storage costs for our test environments. By shrinking the database to an easily portable database, we can refresh test databases swiftly for regression testing purposes. For our customers, it is also a way to start the transition towards a flexible cloud/container-based test environment to meet our CI/CD targets in the future.
We are using a standard software solution with some custom adjustments on an IBM DB2 LUW database. One of our main goals with Datprof's software was to reduce the required data storage by means of subsets. A test database where we previously used a production copy required 23 TB of disk space. By subsetting to a database with the (anonymized) data of 30,000 customers, the disk space has been reduced to only 130 GB. By using the tooling, we therefore only use 0.5% of the original amount of disk space.
The solution is used for: 1. Subsetting test data from/to databases with an incomplete relational model. (With homemade tooling it wasn't possible.) 2. Higher management demanded testing to be done with masked data