Wal-Mart Stores, struggling to translate its brick-and-mortar success to the Web, is using free software named after a stuffed elephant to help it gain an edge on Amazon.com in the $165.4 billion U.S. e-commerce market.
With its online sales less than a fifth of Amazon’s last year, Wal-Mart executives have turned to software called Hadoop that helps businesses quickly and cheaply sift through terabytes or even petabytes of Twitter posts, Facebook updates, and other so-called unstructured data. Hadoop, which is customizable and available free online, was created to analyze raw information better than traditional databases like those from Oracle.
“When the amount of data in the world increases at an exponential rate, analyzing that data and producing intelligence from it becomes very important,” says Anand Rajaraman, senior vice-president of global e-commerce at Wal-Mart and head of @WalmartLabs, the retailer’s division charged with improving its use of the Web.
And then read this story from yesterday:
Wal-Mart Expects Flat U.S. Sales This Quarter
Delayed tax refunds in large part contributed to the slow start of the fiscal year, Wal-Mart U.S. Chief Executive Bill Simon said. At this time last year, Wal-Mart had cashed $3 billion in tax-refund and refund-anticipation checks, he said. It has cashed just $1.7 billion this year.
Some of that tax money is typically spent around Super Bowl time for television sets. Now, the retailer doesn't know how the money will be spent, Mr. Simon said.
Isn’t that a classic problem to be solved using Big Data. I would have thought that with as easy problem statements as “What did our customers do when their tax refunds were delayed?” or “what did they do when they did not buy TVs around Super Bowl”, and with history as old as Walmart’s, it would be easy to figure out customer behavior.
Apparently it’s not.
Or is there more than what meets the eye?
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