For us to sell TDM, we look for specific key differentiators. For instance, TDM only requires a little infrastructure compared to Intel Six, Informatica or other solutions requiring hardware resources. TDM can be connected with DevOps and easily plugged into the DevOps pipeline with the available APIs. Plus, there is an inbuilt automation-friendly API and an inbuilt automation tool to automate the tedious task within TDM.

The benefits of doing something like the data creation is that you are going to be able to totally have control of your data from the get-go. You are not worrying about "what you see is what you get" kind of results from a production set. Instead you are just using all sorts of built-in functions, seed lists, or data calls which are live at that moment to be able to really manipulate your data and create exactly the data set that your testers need. That is very powerful. 

Then on the vTDM side, which is the database cloning, the ability for them to have full control of their environment is the most important aspect of testing sometimes. Now, you do not have to worry about what is on your left, what is on your right, and who you are going to be hurting by trying to do the best testing that you can. Instead you have just you are own set that you can work with. You can spin it up and burn it down when you are done. 

It's really allowed us to focus on the craft of testing, and not focus on the creating data, spending time setting up the scenario that we need, or trying to find that sort of thing. It's allowed us to be more focused on our efforts, it's allowed us to be faster. We run an agile shop, and so we've been able to use that data in our pipeline as we deliver stuff in a CICD world. It's been great.

We have moved data creation from manual or limited and costly automated processes to a set of weekly data builds and an On-Demand offering capable of delivering versatile data that meets the needs of our many teams.

The benefit is that it's something you can repeat over and over again, once a solution is in place. You can benefit from it as often as you want to and without having to constantly looking for support.

This tool is super fast and it has solved many of our issues. It is also much better than many other solutions which are on the market. We've already tested different ones, but this one looks the best currently.

We can deliver, first, securely; second, safely; and third, without extra permissions. We don't need to go through a whole procedure so that developers have permission to access production data. It's not needed anymore. And it will work with production data because it's almost the same data but, of course, not real. The structure of the data is the same and the context of the data is the same but the values are different.

The features are very technical and are definitely what we need. We've got some rules, especially from security, from compliance, but we need to take care of our customer data, very securely, and subtly. There is no other product that gives you these opportunities.

We have certain aspects of our data that we have to self-generate. The VIN number is one that we have to generate and we have to be able to generate on the fly. TDM allows us to generate that VIN number based upon whether it's a truck, car, etc. We're in the car, auto loan business.

We've got a centralized COE in terms of test data management within our organization, benefits that are really three fold in terms of cost, quality and time to market. In terms of the quality we through test data management where, data is kind of the glue that holds systems together and therefore, if I understand my test data, I understand what I'm testing. Through the tooling and kind of the maturity in the tooling we're really bringing an added quality aspect in terms of what we test and how we test, and the risk based testing that we might approach.

In terms of the speed to market, because we don't manually produce data anymore, we use intelligent profiling techniques, test data matching, we massively reduce the time we spend finding data, and we also can produce data on the fly, which turns around test data cycles. In terms of cost, because we're doing it a lot quicker, it's a lot cheaper.

We have a centralized test data management team that caters for all development within my organization. We've created an organization that is so much more effective and optimized in terms of the kind of the time to get to test execution, to identify data and get into execution in the right way.

It allows us to create a testing environment that is repeatable. And we can manage the data so that our testing becomes automated, everything from actually performing the testing to also evaluating the results. We can automate that process. Plus, we're no longer using production data.

The benefit is that it removes manual intervention. A lot of the time that we've spent previously was always manually, as an individual running SQL scripts against databases, or manually going through a UI to create data. These solutions allow us to incorporate automation and self-service to eliminate all of our manual efforts.

It has really changed the culture in the company because nobody could ever imagine generating millions of records. Even production systems have just a couple of million records. When you want to test your applications with three or four times the production load, you can never actually achieve it because there is no other way besides synthetic data generation. You can’t have that volume of data in your DBs. Even if you subset your entire production, you would get just one X of it. To get three or four X of it, you have to go to either data cloning or to synthetic data generation.

If you take DevOps as an example, suppose development has happened and the binary code has been deployed to a certain server. To do continuous testing or continuous integration, you need the test data. CA TDM has a feature where it can generate the required data beforehand and keep it with your test cases however you need it. If you are using JIRA it will put the test data in JIRA. If you are using ALM it will give data to HPE ALM. Once you are running your test cases in an automated way, the data is already there. 

And the data provided will work for all the results. For example, if you want to do a set of automated scenarios, it will work with that. If you want it to work with various regression cycles, it will work with that. And the same data, or maybe a different set of data that you provide, will work with the unit cycles as well. CA has the ability to provide all the data on-demand as well as on the fly.

While we are testing, when there is data that's not accessible or we need to quickly generate data, TDM comes in handy. We can create batch files as well. We can write scripts which automatically create data and we can integrate it with the automatic Dev scripts. This feature is very good. We have used these kinds of features for smaller solutions, although not at a very large scale, because of the complexities involved in the enterprise-level data.

The benefits are that TDM allows us to find the right test data for the test that we need, and then it also allows us to get the required data inputs into our API test, so that we can do a full test.

CA TDM is valuable for us because we use relational databases where it's problematic to sustain the relationships, foreign keys, and indexes. TDM obeys all the relationships and does the masking and data generation according to those relationships. 

Also, the testing team is using TDM to write the rules. Using this tool, our knowledge of data discovery skills has increased. That is an advance for our company.

In terms of performance testing, before TDM, preparing the data and data generation took a week for 20,000 sets of data. Now, with TDM, it takes just one day, which is great. We haven't had much experience with masking yet, we are in the adaptation phase, but data generation has increased our performance by about 60 percent.

On-time production and real time data for DevOps testing environment and CI/CD pipeline.

• Scalability
• The ability to have multiple pieces of information on the same screen. 

When I look at the return on investment, there are not only huge financial gains on it. In fact, when I recently ran the numbers, we had about $1.1 million in savings on just the financials from 2016 alone. What it came down to is, when we started creating our data using Test Data Manager, we reduced our hours used by about 11,800 in 2016. That's real time. That's a significant, tangible benefit to the company.

When you think about it, that's somewhere around six employees that you've now saved; let alone, you have the chance to focus on all the different testing features, instead of having them worrying about where they're going to get their test data from.

CA Test Data Manager is enormously helpful to us. We assist our customers by speeding up the application development process using real-time test data and synthetic test data, which mimics the real test data.

By using this product we are able to provide test data for the development and testing teams. It has removed the dependency of making production data available for development and testing activities. Using data masking techniques we can comply the rule of non-disclosure of personally identifiable information

Now, though, my company is going through a process to be more agile, which is basically the theme of a recent CA conference I attended. While we are trying to go through the agile journey, there are some building blocks that need to be in place. Test data in the whole product lifecycle, is very, very important; how good is the data that you have; how efficiently you can run those test cases, again and again, repetitively, which is very important; and I guess the features that TDM gives fit right into that; what we are looking for, in the journey that we are having.

It doesn’t only cover our data masking needs, but also our data subsetting and synthetic data generation needs. Finally, it gave us the idea of making test data as a service within our organization.

We realized before what we are looking for. Now, we are trying to get everybody to work with the DevOps mindset. That is the main advantage and benefit that we are seeing here.

We are still in our DevOps build out phase. However, it will allow us to have quicker releases, more frequent with smaller content, as well as speed up our testing.

This data is a very, very important thing because there are a lot of challenges around this data right now and it's very complex. Creating test data right from scratch is going to be complex. But with the Data Finder's synthetic data generation, the whole copy is created and then on top of it all the data manipulation is done. 

It is just easy to manage from what I have seen so far.

Automation tests are more stable so they can be run more continuously.