The idea of infinitely scalable, self maintaining, searchable object storage in the cloud is a great idea – if you can make use of it. If an enterprise is able to create a use case around this resource, then they have an unlimited supply of storage capacity. The question is: what can enterprise-level company do with object storage? Enterprise use cases include data monetization through big data projects, compliance with the long-term storage requirements of certain regulations, and operational expenditure savings by slimming down primary storage.
Data monetization is a relatively new concept in IT, but it shows a lot of promise for many companies. The question is can data create additional revenue or savings when taking a different look at that data from its original creation?
For example, suppose a company knows that a machine on an assembly line just malfunctioned. This data is relevant at that moment, and will go to some type of maintenance operation that will investigate and repair as necessary. However, storing all of the times that a particular device malfunctioned could generate other information. Perhaps the machine only malfunctions when it’s running for a certain period of time, or at a certain time of day, or when it has to perform a particular function. An assembly line can create hundreds of thousands – if not millions – of data points available for review in a variety of ways to determine trends useful to increase product quality and lower maintenance costs. Storing that amount of data, however, is not easy.
There are a variety of regulations that require storing certain types of data for certain periods of time, such as the requirement for some companies to keep their email for seven years. The Feds require trading firms, for example, to store a copy of all communications with clients, including emails, phone calls, and instant messages. Such data can be stored in a typical file system or in a tape-based system, and it can also be stored in an object storage system. Storing it in an object storage system creates a number of interesting possibilities in terms of ensuring that the data will always be accessible to anyone that needs it.
One idea is the creation of a simple query system that allows a person to retrieve any communications they had with a given client, or around a given vendor. Given appropriate permissions, of course, financial analysts or their managers could easily retrieve everything said about a given stock, or all recommendations about a specific stock to a particular investor. Having data in an object storage system also creates the possibility of data monetization projects that could create correlations between different events using some aforementioned big data techniques.
Finally, one of the easiest ways for a company to leverage object storage is to use it to “thin out” primary storage. That is, to clean out of the primary storage system any data that IT isn’t actively using and store the data in an object storage system. This creates immediate operational expenditure savings by reducing the amount of primary storage the enterprise has to maintain, power and cool. In addition to the money savings from in the primary storage area, there is an associated reduction in the backup system costs since the enterprise no longer has to backup data from the primary storage system.
In addition to sending out primary storage, moving lesser used data into an object storage system once again creates data monetization possibilities. This is due to the searchable nature of most object storage systems.
Enterprises wishing to reduce their cost of primary storage, in addition to creating additional revenue via data monetization projects, can easily leverage object storage. Once the data goes into the object storage system, there are myriad ways an organization can monetize it by searching through it and looking for trends. Therefore, the question is not whether enterprise environments can leverage optic storage. Instead, it is simply when they will begin to do so.
Sponsored by Dell EMC