DATPROF Reviews

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 haven't yet implemented the solution. So, at this time, the benefits are none, but the benefits that are foreseeable in the next two years would be enormous. It would simplify our test data operations. Currently, there are no end results as such with respect to our users, but we see the potential, and that's why we are happy to proceed with it.

It would be the most important part of testing within the organization. The capabilities that DATPROF provides will be more and more integrated into the day-to-day testing activities of business users or DevOps teams.

We are protecting our personal and sensitive information, while we provide test data to our customers for their business-as-usual and project testing.

One of the ways DATPROF has added value is that three years ago, before we had the solution, when an audit was done for non-SAP applications, there were always red flags. We, as a company, were not able to protect the data. The demand for doing so was there, but in big organizations you need the willingness as well. Once we found  DATPROF, the red flag issue was eliminated. Audit-wise, we are now compliant.

And our customers are also happy because when they do any kind of project, it's not only about internal users because the systems are being exposed to multiple external people. That is where we are now able to protect our data.

For non-SAP, before we had DATPROF, we used a couple of workarounds. For example, we would write an SQL query to change a phone number from A to B, but for all phone numbers. If we had 40,000 customers and 40,000 phone numbers and wanted to mask the phone numbers, we would write a query to change all the phone numbers to 123-456-7890. But that's not scrambling, that's just a mass change, and it was manual work. Now, the results we get do not look like masking because it's real masking.

We use it for scrambling personal data. That's the most important use case that we have. We both have SAP and non-SAP applications.

Two or three years ago, before DATPROF, we did not have the ability to scramble or mask data in our non-SAP applications. Doing so was only a dream. Today we are confident that our customers' sensitive data is not in anybody else's hands. Production users, even developers, were usually able to see personally identifiable data in test environments because they have super-user access. But now we don't have that situation anymore. Anybody who logs in to test data only sees scrambled data. They don't see the real data.

Overall, DATPROF has simplified our test data operations, absolutely. Before we had the ability to scramble, we did not copy our production data into our test system because we didn't have any way to protect our data. Today, because we have a scrambling solution, we are able to do refreshes frequently, meaning production data comes into the test system very frequently. That makes it possible for the testers to do testing with the real production-like data. As a result, our testers are able to test efficiently and that helps us avoid production incidents.

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.

DATPROF helped improve our organization because as more of our development teams adopt the tool, we become faster at creating test data. The test data quality is also improving, resulting in us creating better products. Overall, we gain time by speeding up the creation of test data and increasing the quality of our products. 

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 improvements we have made within our organization are very diverse; we've reduced the amount of disk space for test data to just 0.5 percent of the original amount. That means enormous cost savings.

Due to the availability of a ready-made database for testing, the lead time to set up a test environment has become much shorter.

In addition, by anonymizing we comply with the GDPR and we run less risk of the loss and/or misuse of our customers' data.

This makes us even more future-proof and frees up time to focus on other important things.

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

We organized a TDM process with both DATPROF Subset and Privacy, fully self-service and fully automated with ServiceNow, Runbook, and Ctrl-M. Within 15 minutes users can establish a refreshed testing environment.

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.    

A small test database is essential for us to move forward for provisioning the development teams with dedicated test environments with test data fit for their purposes.

The database had been thus far maintained by the software supplier. The easy access and analysis options to judge the data model of the complex database gave us the freedom to maintain the test data without the help of our supplier.

Our customer's IT department has limited technological knowledge. Understanding the database was the first step in becoming self-sustainable.

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.

Our previous tool for masking sensitive test and development data was only able to mask Oracle databases. With DATPROF Privacy and DATPROF Runtime, we are also able to mask SQLServer, MySQL, and Postgress databases. As a result, DATPROF made it possible for our organization to be compliant with the GDPR.