The volume of digital information continues to skyrocket. In all its forms, including structured, unstructured, emails and text messages, data is expected to grow by 30,000 percent around the globe by 2020. How will your organization archive and index today's information, along with previous late-stage information, to be readily accessible by users in the decades to come?
Even a corporate giant such as General Motors is acutely aware of these challenges. Congress is asking the company why it took 10 years to recall a defective part that has allegedly led to the deaths of 13 people. This inquiry has broader implications than simply interrogating archived manufacturing systems. It also includes accessing related unstructured operational and regulatory documents along with access to employee email accounts to determine who authorized what changes to which parts, why existing customers were not notified, and what was the chain of command and decision-making process.
Ultimately, corporations are held responsible. What is your company's plan to capture, organize, store, manage and protect disparate data across the enterprise to meet future customer and regulatory requirements? Smart companies are creating strategies and building solutions for intelligent archiving systems.
Even companies operating in regulatory industries continue to store data on dispersed and deteriorating tapes. The risks associated with not properly maintaining archived data can have dire consequences. There also are problems arising from data volume, velocity and variety in the early and middle stages of the lifecycle. What should the enterprise do with late-stage data and how should it be managed?
In this slideshow, Srini Mannava, founder and CEO of Infobelt, a leading developer of information lifecycle management solutions, takes a closer look at the data storage lifecycle and four key features that should be at the core of an intelligent archiving solution.
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