Joe works as a backup administrator for XYZ company. XYZ has been using Druva Phoenix for about 1 year. It intends to expand the data footprint for Phoenix by protecting additional resource types and purchase additional credits. Hence, Joe has been requested for an analysis of the trend of storage consumption and data growth for the infrastructure.
Joe looks at the Analytics page and he can figure out the credit balance and the estimated time left for credit exhaustion. The page provides an overall summary with respect to the amount of data they have been protecting with Phoenix. Joe aims to understand the data growth for the resource types being currently protected, which will help his organization understand the number of credits they would require in addition to the new resource types that they plan to protect.
He wants to know about the servers that are contributing the most to the storage consumption. Hence, he goes to the All Backup Sets section and views the backup sets appearing in descending order of storage consumption. Here, he can also view the average change rate for each backup set, thereby getting an overall understanding of the data growth.
He views the Current Source Data graph and looks at the events that have taken place during the last 30 days. This graph helps him ascertain the contribution of each resource type to the storage consumption. He clicks an event marker on the timeline to know the changes that were made on a particular day. The event details appear and he can see the backup sets that were added, deleted, or modified. The list of new backup sets helps Joe ascertain any recently added backup sets that are consuming more than estimated storage. He takes note of these backup sets.
Using these statistics available with Analytics, Joe and his organization assess their infrastructure deployment and predict the number of credits they would need in the upcoming fiscal year.