DataStage facilitated our peak data integration projects. For example, big data integrations have happened, particularly when we worked with BigQuery files... that integration server.

DataStage parallel processing capabilities have improved data tasks. When I worked with DataStage, it could handle around two terabytes of data. We have other appliances as well, but we're processing data concurrently. It was good. My team supported it well, and everything worked fine.

The GUI was good. Compared to Cloud Pak for Data, we have some enhanced connectors in the standard InfoSphere DataStage version. That standard version is really good; it's easy to use.

When we want to find out the absolute quality of data, the governance features really helped. For example, when we tried to identify discrepancies between systems, it worked well.

The product has improved our organization by allowing us to provide the product to clients as a reliable data management solution.

I have worked during many implementations using DataStage. All of the projects that I worked on have been successful. This is due mainly to the strict discipline around best practices, and by following a set of standards and templates designed to reduce complexity and improve automation, including strong reference architecture.

It improves how our client's organization functions.

The solution has improved the time it takes to perform tasks related to batch applications.

Our main goal of this project is to increase the efficiency of the usage of this solution and help the bank to get money from the data.

It's standardized our batch integration.