Virtualized Data + Storage Make a Perfect Match

Virtualized Data + Storage Make a Perfect Match

Posted in tech

Today’s enterprise has plenty of storage types to choose from, but it’s a challenge to find the right storage resource for evolving data demands. Different types of data need different levels of performance and protection, and it’s difficult to ensure data is stored in the right place at the right time. It’s even harder to move data as those demands change.

Hot Data Likes Hot Dates

As we head into Valentine’s Day, it’s an interesting time to compare the relationship between data and storage to human relationships. Data needs, just like human needs, evolve over time. New data often starts out in development environments. Like a first date, there’s lots of working to feel out what data will need. Initial production deployments are high energy, and get matched with storage that can meet its demands. This stage can be a costly part of any relationship, and data is no exception. Mature data requires stability and data protection to ensure business continuity; retired data needs safety and low cost. But today, data typically never gets moved off its initial infatuation storage, which creates an expensive disconnect between resources and demands.

Primary Data’s DataSphere platform acts as the matchmaker of the datacenter. Through data virtualization, DataSphere creates a single, storage-agnostic dataspace. This sets data free to automatically move from one storage type to another according to IT-defined policies.  Matching data to the resource that meets its current needs maximizes your existing storage investments by efficiently utilizing each resource to do what it was designed to do best, whether that is fast performance, high security, or low cost.

Adapting to Evolving Data Demands

Matching storage resources to data demands also allows enterprises to reduce overprovisioning to save budget, as high-speed, high-value storage is preserved to store the data that truly needs high performance resources. With DataSphere, IT can keep track of how much storage is really being used, providing valuable insight to adjust policies, while greatly reducing costs.

When new storage does have to be added because of capacity or necessary upgrades, DataSphere makes the process simple. Gone are the days of lengthy planning, purchasing and implementation cycles. Instead, DataSphere allows data to be simply and immediately moved to new storage, according to policy.  

By introducing data virtualization into the datacenter, DataSphere enables enterprises to create a perfect match between data and storage, even as needs change. Human relationships may not be so simple, but at least automating this match up in the datacenter will give IT pros more time to focus on real-world relationships. 

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