What to consider when looking for a data-protection solution

Losing access to key applications and critical business data can be devastating. With downtime costing companies from thousands to millions of dollars per hour in lost productivity and opportunity costs, it is imperative to keep the IT business infrastructure available at all times.

IT departments must meet the challenges of real-time business continuity, disaster recovery, compliance and governance requirements with higher service levels, fewer resources and ever-tightening budgets.

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The need for a complete, high-performance, easy-to-use product for protecting business-critical data is clear. Here are some of the key concepts to consider when you’re evaluating data-protection products:

* Recovery-time granularity (RTG) dictates a data-protection tool’s ability to recover data down to the day, hour, minute or second. The finer the detail, the more control you have over the tool's ability to recover usable data, so RTG is an important parameter for recovering from a logical failure. For example, should a data corruption happen at 10 a.m. while data protection is occurring, the data also is corrupted. A data-protection tool that provides RTG in seconds could recover the data to 9:59 a.m. and 30 seconds, providing a recovery point as close as possible to the logical failure.

* Recovery object granularity (ROG) measures how detailed an object a data-protection product can recover. That may be a storage volume, a file system, a database table, a transaction, a mailbox or even a single message.

* Recovery event granularity (REG) measures the capability of a data-protection tool to track specific events, for example, the opening, closing or saving of a file; and to recover a failed application or data set for a specific event. REG measures how capable a protection tool is at recovering, for instance, to the point of when a specific file was saved. The better the tool's ability to recover to a specific event, the better its REG.

* Recovery consistency characteristics (RCC) defines how well the associated application can use the recovered data. The ability of a data-protection tool to return consistent data depends not only on how data is captured and stored but also on the type of data being protected.

In a true real-time data-protection product -- one that supports robust requirements for detail -- a data object can be at any level of detail and may have hierarchy. Metadata-, time-, and event-indexing capabilities enable tracking of a real-time, continuous object history, locating missing information and recovering objects at different levels of detail.

Data-protection services must be more reliable than the applications they protect. When a data-protection service fails, the data service must fail over to another data-protection instance, such that an application would be protected continuously.

A protection tool also must be secured, so that individuals without the proper authorization cannot configure its policy freely. Unlike an application, a data-protection product should not let any individual alter its protected data. Data history can be purged only by policies.