Bridging Storage Infrastructure to Business Value
Engage enterprise-level information management for cost-effective storage of big data repositories
Big data: it’s big, it’s growing, and it’s here to stay. And its ongoing growth is impacting organizations across many industries. Healthcare organizations, for example, are reporting significant annual growth in their distributed storage costs and infrastructure. As the need for storage continues at an ever-increasing pace across many industries, enterprises should take a step back and consider the key purpose of storage technology—containing data. This purpose forms the foundation for developing effective information management initiatives.
Data is indeed flooding into data centers from a variety of avenues including the Internet of Things, social media, marketing campaigns, and other channels. And without question, it will continue to stream into organizations at an ever-expanding rate. That data needs to be aggregated, synthesized, and analyzed to provide the information that offers key business insights and is quickly becoming an important asset in today’s organizations.
According to a recent Gartner report, "the rapid growth in unstructured data, which is increasing at 60 percent to 80 percent year over year, and the need to store and retrieve it in a cost-effective, automated manner, will continue to drive the growth of object storage.1 This growth is creating a challenge to store big data in a readable and accessible format that applications can use and business executives and stakeholders can mine to gain insight for growing their businesses. While procuring additional storage is certainly an obvious technical solution, the costs of maintaining and administering storage to keep pace with this growth render that option a poor choice economically.
Pacing capacity with the rise of big data
How can storage capacity possibly keep up with the high tide of data flooding into storage infrastructure? To help curb the steady rise of capital expenditures for storage while making the data readable and accessible requires organizations to sharpen their information management practices through information governance, policies, and processes. Information management enables organizations to effectively mine their big data repositories and bridge the services provided by storage infrastructure with the needs of the business.
Rationalization of data—defined as identifying and deleting duplicate files, archiving legacy files, and cleaning up database white space—offers a good first step toward managing data at an enterprise level. For example, enterprises often find multiple backups of files that were replicated from the primary data center to the secondary data center, and then backed up again in the secondary data center. By removing or archiving data, which in this way is offering little or no business value to the organization, expanded storage space becomes available for incoming data.
In addition, establishing storage tiers, information classes, and storage classes of service can go a long way toward enhancing the management of big data. These tactical efforts should be well documented, reviewed, and repeated at regular intervals, particularly as storage technologies and business practices evolve.
Applying resource-efficient information management
A key benefit of a well-applied information management strategy is implementation of enterprise-level governance and policies that offer suitable, long-term provisioning of capital, operational resources, and budgets. Information governance should dictate how often storage tiers and classes are reviewed and refined, and it should hold information owners accountable for the information services they request.
Policies can enforce and define scheduling for purging duplicate files and establishing which controls should be put in place to protect valuable data. Policies also help ensure that data is backed up appropriately and that only the necessary backup sets are retained.
Together, information management governance and policies help ensure that data is stored, backed up, replicated, migrated, archived, and deleted in a highly efficient and economical manner that is well suited for the organization. Enterprise-level information management can span platform towers and establish a bridge between the IT organizations that provide the infrastructure and the parts of organizations that mine and analyze big data.
Frequently, an information management plan requires changes to organizational strongholds such as the number of resources that are allocated to any one department, or which part of the organization is responsible for backing up data. When information management is planned and executed properly on an enterprise level, an organization’s storage resources, capital, and operating budgets are well positioned to meet the ever-increasing demands of big data streaming into the enterprise’s data centers. In turn, organizations can realize the benefits of mining data from their big data repositories and gaining insight from analysis of that data.
An IBM financial organization client, for example, recently reported it could delay procuring tier 1 storage by implementing an information management approach for the continual increase in data streaming into its data center. Organizations can maximize insight and the availability of key information by engaging in an enterprise-level information management strategy that includes developing information governance and mapping business requirements to the storage infrastructure. In this way, information management helps organizations combine the purpose and design of storage infrastructure for the critical informational needs of the business.
* “Predicts 2014: More Storage Capacity and Efficiency, Less Cost - Managing Infinite Data from Every Direction,” G00258359, Gartner Inc., December 2013.