GET MORE FROM THE CLOUD. GET VANTAGE.

In many organizations, the capacity of test and development systems is often under-utilized - but when activity picks up, capacity can be under-sized. This paradox can be addressed with cloud deployment. The flexibility to allocate exactly the resources you need for testing and/or development, then turn around and de-allocate just as quickly is very powerful. An added advantage for test and development is the ability to use the latest versions of software for feature exploitation and/or validation before the software is ready to be deployed in a highly governed on-premises environment.

In data lab deployment, cloud implementation has two big advantages. First, scalability in cloud provides the perfect working model for users who cannot necessarily anticipate resources needed for working with the next new data set or algorithm. The second advantage of cloud deployment for data science work is agility. Internal process and timeframes for bringing in a new piece of software on-premises can slow down data discovery. In a cloud data lab environment, the desired tools are more easily accessible, even without going through a maze of IT governance and standards committees.