ASE Data Compression: Doing More with Less

Improving Performance and Reducing Costs Even As Data Stores Mushroom
The proliferation of data across enterprises, including data residing in operational, development and back-up systems, siloed departmental systems and on individual desktop, laptop and mobile devices is nearly unfathomable. In a digital blink of an eye, organizations have blown quickly through the megabyte and gigabyte ages and now straddle the terabyte age. A few organizations have even crossed the petabyte threshold. Like the expansion of the universe, it seems as if this data growth will continue unchecked.

Studies show an overall annual data growth of more than 30 percent. In the face of this unrelenting and rapid accumulation of data, quips that “storage is cheap,” don’t do much to alleviate the concern among IT professionals and corporate executives that there is, in fact, a rather steep price to pay for this growth.

When you consider the multiple factors that make up the total managed cost of enterprise data — including storage hardware, licensing, facility space, cooling and other energy costs, staffing and maintenance, it doesn’t take zettabyte data stores to cause significant budgetary pain.

In a recent survey of Sybase customers, more than 30 percent of respondents reported they have terabyte-sized databases. They also reported that their annual cost to manage a single terabyte of data ranged between $25,000 and $100,000. The non-stop growth of data stores due to the acquisition of new data (much of which is space gobbling unstructured data), longer data retention regulations, siloed departmental data, replicated data for backups and use in development and testing environments, presents organizations with other types of costs as well. These additional costs manifest themselves in the form of operational performance degradation, slower back-ups, increased system downtime and maintenance requirements, and business-critical reporting and analytics challenges. After all, it doesn’t do an organization much good to collect huge volumes of data that it can’t efficiently organize, store, access, query and analyze in order to make insightful and rapid business decisions and provide superior customer service.

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