Sanjay Singh, formerly of Abercrombie & Fitch and Procter & Gamble, will head up a new data-analysis business unit.
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Goodwin places stored data into three categories, based on descending order of importance. The highest category, which he terms mission critical data, is information that must be recovered within a short time frame-say, four hours or less, so as not to disrupt operations critical to a company’s success. The two most important examples for retailers: POS data and inventory levels, information crucial to process orders and serve customers without losing sales.
The second category is business critical information, data crucial to operating a company on a daily basis but that the temporary loss of which won’t result in lost revenue or sales. “Back-office financial accounting data is business crucial; you’ve got to have it, but if you close the books today or tomorrow it’s not as important as keeping your POS operation moving,” Goodwin says. Business crucial data, he adds, might be set in storage for a maximum retrieval time of 12 hours.
Less important data--which could entail customer loyalty program information, product lifecycle records or old POS data kept for long-term backup-constitute the third tier and might be set for a retrieval time of a few days.
Within the data storage vendor community, Goodwin notes that the high-end servers with the fastest data transmission performance and deepest reliability are Hitachi Lightning, EMC Symmetrix, Hewlett-Packard EVA and IBM Shark systems. He places within the mid-range of storage servers EMC Clariion and IBM FastT, and within the low-end, Dell Power Edge, EMC Sentera - though he notes that Dell is also moving into the mid-range.
In addition to segmenting of data by importance, vendors are developing other ways to save money with data storage systems. Acxiom Corp., for instance, offers a system of computing power from a grid of computer processors it maintains for clients. In the second quarter of this year, it expects to make available a grid-based storage system that clients can tap. By using low-cost components in a grid environment that mirrors data for reliability, Acxiom says it can provide data storage at about $5,000 per terabyte of data, compared to $30,000 to $40,000 per terabyte for more conventional storage systems. “This will make a lot of storage available that might otherwise be cost-prohibitive for some retailers,” says Alex Dietz, products organization leader.
While investments in data storage systems often favor a single vendor platform to assure the best integration, the evolution toward open architecture and common industry standards is making it easier to for different vendors’ systems to work together. “Most of the differences in the market have disappeared,” Steinhardt says.
That stronger integration is also making it easier to connect storage systems to sources of data. “It’s very much plug-and-play,” Steinhardt says. “We make products now so you don’t have to make changes to an existing application server environment.”
But retailers still need to conduct due diligence in checking different network components to assure a smooth flow of data. “You have to look at the entire spectrum of the IT solution and match processors with storage systems and communication networks, because the system will never be faster than the slowest bottleneck,” Steinhardt says.