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QUINCY, Mass. -- Ahold USA should shortly have the terabyte tiger by the tail, as it installs and implements a faster, more robust customer data warehouse platform this year.
As part of its strategy to optimize store operations, increase profitability and improve customer experience throughout nearly 1,200 supermarkets, the company will deploy the enterprise-class Netezza Performance Server data warehouse appliance from Framingham, Mass.-based Netezza.
Ahold said it selected the NPS system to perform faster, more complex analyses of its terabytes of customer and operational data for its store banners, which include Stop & Shop, Tops Markets, Giant-Carlisle, and Giant-Landover. "We plan to use the system to perform market basket analysis with the goal of increasing sales and reducing costs," Al Clevenger, Ahold USA's dir. of data management, data warehousing services, told Progressive Grocer.
By replacing its legacy CDW systems with the NPS data warehouse appliance, Ahold will be able to run a wide variety of interactive analyses, while dramatically reducing query times. "The old system's shortcomings included poor report performance and availability, and it was a complex environment to support," Clevenger said. "Some of the improvements we'll see with the new system are an improved report performance, more system time available because of less system maintenance and downtime, lower TCO, data freshness, and an increase in data volume. The NPS system delivers the increase in performance we wanted without causing us to re-engineer our entire CDW. Now, we can achieve results in minutes instead of hours, eliminating stale data and enabling us to be even more flexible and targeted with our decisions."
The Netezza Performance Server system is an enterprise-class data warehouse appliance that architecturally integrates database, server and storage in one appliance. By placing processing power at the disk level, analysis occurs at the source at streaming speeds -- analyses that took hours now take just seconds. The NPS system combines commodity hardware components with Linux and an open source database, resulting in dramatically lower total cost of ownership.
-- Joseph Tarnowski