We primarily use the solution for data warehousing.
Primarily what happens is, in Juniper, they have internal business analytics and intelligence, a business intelligence analytics dashboard, and a lot of databases that capture the customer feedback.
It actually captures all the internal defects that are tracked on products. There are different databases that accumulate all this data. Basically, you need to be able to source the data and do some filtering. We extract, transform, and load logic. We have to run certain business rules based on what the program or management team looks at. The teams want to filter out some of these problems that they have, and they want to analyze how well the company is responding to many of these customer issues, et cetera.
Our company is a large company with each particular team using its own database and its own database tables. It becomes extremely hard for the company to take the data from different data sources and be able to correlate everything and be able to analyze many of the processes that are happening within. There is a workflow discontinuity that has been observed due to the fact that the data is distributed. In order to understand exactly how a request comes in from the customer and what goes on behind the scenes in order to resolve the problem or to be able to provide the support to the customer, and how long does it take before the problem gets fixed and delivered, et cetera, we need to centralize everything and we use data warehousing for that.
There are other similar kinds of business rules filtering that happen on the dashboard as well. This enables people to be able to view the data that is needed and the metrics that are of interest to them and is especially useful when it comes to the executive team.