Big Data at Sears
When it comes to the adoption of information technology, Sears was years ahead of most retailers, implementing an enterprise data warehouse in the 1980s while most retailers were still relying on manually-updated spreadsheets to examine their sales numbers. These days the company is using big data technologies to accelerate the integration of petabytes of customer, product, sales, and campaign data in order to understand increase marketing returns and bring customers back into its stores. The retailer uses Hadoop to not only store but process data transformations and integrate heterogeneous data more quickly and efficiently than ever.
“We’re investing in real-time data acquisition as it happens,” says Oliver Ratzesberger, Vice President of Information Analytics and Innovation at Sears Holdings. “No more ETL. Big data technologies make it easy to eliminate sources of latency that have built up over a period of time.”
The company is now leveraging open source projects Apache Kafka and Storm to enable realtime processing. “Our goal is to be able to measure what’s just happened.” The company’s CTO, Phil Shelley, has cited big data’s capability to decrease the release of a set of complex marketing campaigns from eight weeks to one week—and the improvements are still being realized. Faster and more targeted campaigns are just the tip of the iceberg for the retailer, which recently launched a subsidiary, MetaScale, to provide non-retailers with big data services in the cloud.
Source: Big Data in Big Companies, Thomas H. Davenport and Jill Dyché, May 2013 (Go to Suggested Readings to view full article)
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